犰狳中有效的稀疏矩阵加法

I am trying to construct a sparse matrix L of the form

我正在尝试构造一个表格的稀疏矩阵L.

L and Hi are respectively a very sparse matrix and row vector. The final L matrix should have a density of around 1 % .

L和Hi分别是非常稀疏的矩阵和行向量。最终的L矩阵应具有约1%的密度。

Armadillo provides a arma::sp_mat class that seems to suit my needs. The assembly of L then looks like this

Armadillo提供了一个似乎符合我需求的arma :: sp_mat类。然后L的组装看起来像这样

    arma::sp_mat L(N,N);
    arma::sp_mat Hi(1,N);

    for (int i = 0; i < p; ++ i){

    // The non-zero terms in Hi are populated here

    L += Hi.t() * Hi;

    }

The number of non-zero elements in Hi is constant with i. I do not have much experience with sparse matrices but I was expecting the incremental assembly of L to be relatively constant in speed.

Hi中的非零元素数量与i不变。我对稀疏矩阵没有多少经验,但我期望L的增量装配速度相对恒定。

Yet, it seems that the speed at which Hi.t() * Hi is added to L decreases over time. Am I doing something wrong in the way I assemble L? Should I preconstruct L by specifying which of its components I know will not be zero?

然而,似乎Hi.t()* Hi加到L的速度随着时间的推移而降低。我组装L的方式有问题吗?我应该通过指定我知道哪些组件不会为零来预构建L?

1 个解决方案

#1

It seems that L is not initialized so that it effectively changes size when incremented with Hi.t() * Hi. This was likely the cause for the decrease in the speed.

似乎L未初始化,因此当使用Hi.t()* Hi递增时它会有效地改变大小。这可能是速度下降的原因。