特征库，使用稀疏矩阵的简单线性代数运算增加了它们的分配大小

Question

I am relatively new to Eigen, and am facing the following issue when using sparse matrices in Eigen.

When I use the below code, the allocatedsize for the variable C increases to 20 after addition. I am lost as to why is this happening.

Eigen::SparseMatrix< double > A( 10, 1 );
A.reserve( Eigen::VectorXi::Constant(1,3) );

A.coeffRef( 2, 0 ) = 2;
A.coeffRef( 3, 0 ) = 3;
A.coeffRef( 7, 0 ) = 7;

Eigen::SparseMatrix< double > B( 10, 1 );
B.reserve( Eigen::VectorXi::Constant(1,3) );

B.coeffRef( 0, 0 ) = 0;
B.coeffRef( 1, 0 ) = 1;
B.coeffRef( 8, 0 ) = 8;

Eigen::SparseMatrix< double > C( 10, 1 );
C.reserve( Eigen::VectorXi::Constant(1,6) );

C = A + B;

Answer 1

It looks like in assign_sparse_to_sparse there is a line

temp.reserve((std::max)(src.rows(),src.cols())*2);

and afterwards, temp is moved to the actual destination. That means, prior reserving (and resizing) in your case does not help. I'm not sure though, why temp is not reserved to nonZerosEstimate() of the corresponding evaluator.

Independent of that, if you are working with N x 1 sparse matrices you should consider switching to SparseVector<double> instead.