从Eigen :: SparseMatrix提取块/ROI，无需复制 [英] Extracting blocks/ROIs from Eigen::SparseMatrix without copying
问题描述
我想知道是否有什么好方法可以从Eigen :: SparseMatrix提取块/ROI? 更准确地说，我要提取的是内部向量.
I wonder is there any good way to extract blocks/ROIs from Eigen::SparseMatrix? More precisely, what I want to extract is inner vectors.
我想做的事情是这样的:
What I want to do is like:
typedef Eigen::SparseMatrix<double,Eigen::RowMajor> SpMat;
// Prepare some sparse matrix
SpMat spmat;
// Extract lines from it
const SpMat& row_i = spmat.innerVector(i);
const SpMat& row_j = spmat.innerVector(j);
// Some calculation with row_i and row_j...
如我所测试的，row_i和row_j的数据是从spmat中复制(!!)的.
但是，显然，它效率低下.
内部向量的数据(特别是row_i.m_data.m_values和row_i.m_data.m_indices)是原始数据(分别是spmat.m_data.m_values和spmat.m_data.m_indices)的连续部分，因此应该有更聪明的方法.
As I tested, the data of row_i and row_j is copied (!!) from spmat.
However, obviously, it is inefficient.
The data (esp. row_i.m_data.m_values & row_i.m_data.m_indices) of inner vectors is continuous part of original data (spmat.m_data.m_values & spmat.m_data.m_indices resp.), so there should be smarter way.
我也许可以实现一种新方法来做到这一点，但这需要我艰难地研究源代码.所以我不想.
I may be able to implement new method to do this, but it require me a tough digging into the source code. So I don't want to.
任何帮助都将不胜感激！ 预先感谢.
Any help is grateful! Thanks in advance.
推荐答案
您可以使用c ++ 11 auto关键字将row_i和row_j声明为真正的读写表达式，也可以使用适当的类型:
You can either use the c++11 auto keyword to declare row_iand row_j as true read-write expressions, or use the proper type:
const auto row_i = spmap.innerVector(i); // C++11 version
const SpMat::InnerVectorReturnType row_i = spmap.innerVector(i); // C++98 version
此外，不是默认情况下SparseMatrix存储在main列中，因此内部向量"是一列.如果要引用行，则必须使用行为主的存储布局:
Moreover, not that by default a SparseMatrix is stored in column major, therefore an "inner-vector" is a column. If you want to reference rows, then you have to use a row-major storage layout:
typedef Eigen::SparseMatrix<double,RowMajor> SpMat;
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