切片scipy.sparse矩阵的最快方法是什么?

问题描述

我通常使用

matrix[:, i:]

它似乎没有我预期的那样快.

It seems not work as fast as I expected.

推荐答案

如果要获取稀疏矩阵作为输出，执行行切片的最快方法是使用csr类型，对于列切片csc ，在此进行详细介绍.在这两种情况下，您都只需要执行当前操作即可:

If you want to obtain a sparse matrix as output the fastest way to do row slicing is to have a csr type, and for columns slicing csc, as detailed here. In both cases you just have to do what you are currently doing:

matrix[l1:l2,c1:c2]

如果要输出其他类型，可能有更快的方法. 在另一个答案中，它解释了许多切片矩阵的方法以及它们的不同时序.例如，如果您希望将ndarray作为输出，则最快的切片是:

If you want another type as output there maybe faster ways. In this other answer it is explained many methods for slicing a matrix and their different timings compared. For example, if you want a ndarray as output the fastest slicing is:

matrix.A[l1:l2,c1:c2]

或:

matrix.toarray()[l1:l2,c1:c2]

比:

matrix[l1:l2,c1:c2].A #or .toarray()

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