有没有一种有效的方法来连接scipy.sparse矩阵? [英] Is there an efficient way of concatenating scipy.sparse matrices?

问题描述

我正在处理一些相当大的稀疏矩阵(从5000x5000到20000x20000)，并且需要找到一种灵活的方式来连接矩阵的有效方法，以便从不同的部分构造随机矩阵.

I'm working with some rather large sparse matrices (from 5000x5000 to 20000x20000) and need to find an efficient way to concatenate matrices in a flexible way in order to construct a stochastic matrix from separate parts.

现在，我正在使用以下方式来连接四个矩阵，但是效率非常低.有没有比不转换为密集矩阵更好的方法了?

Right now I'm using the following way to concatenate four matrices, but it's horribly inefficient. Is there any better way to do this that doesn't involve converting to a dense matrix?

rmat[0:m1.shape[0],0:m1.shape[1]] = m1
rmat[m1.shape[0]:rmat.shape[0],m1.shape[1]:rmat.shape[1]] = m2
rmat[0:m1.shape[0],m1.shape[1]:rmat.shape[1]] = bridge
rmat[m1.shape[0]:rmat.shape[0],0:m1.shape[1]] = bridge.transpose()

推荐答案

稀疏库现在具有 vstack 分别用于水平和垂直连接矩阵.

The sparse library now has hstack and vstack for respectively concatenating matrices horizontally and vertically.

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