在Matlab中稀疏矩阵分配变得非常慢 [英] Sparse Matrix Assignment becomes very slow in Matlab

问题描述

我正在用来自文本文件的值填充稀疏矩阵P(230k，290k)，我逐行读取，这是(简化的)代码

I am filling a sparse matrix P (230k,290k) with values coming from a text file which I read line by line, here is the (simplified) code

while ...
            C = textscan(text_line,'%d','delimiter',',','EmptyValue', 0);
            line_number = line_number+1;
            P(line_number,:)=C{1};
end

我遇到的问题是，在一开始的时候

the problem I have is that while at the beginning the

P(line_number,:)=C{1};

语句很快，几千行变得非常慢之后，我想是因为Matlab需要找到每次分配的内存空间.有没有一种方法可以用稀疏矩阵预先分配内存?我不这么认为，但也许我错过了一些东西.

statement is fast, after a few thousands lines become exterely slow, I guess because Matlab need to find the memory space to allocate every time. Is there a way to pre-allocate memory with sparse matrixes? I don't think so but maybe I am missing something. Any other advise which can speed up the operation (e.g. having a lot of free RAM can make the difference?)

推荐答案

到目前为止，生成稀疏矩阵的最快方法是同时加载所有值，然后在一次调用.您必须加载数据并将其安排到定义每个已填充单元格的行索引和列索引以及值的向量中.然后，您可以使用S = sparse(i,j,s,m,n)语法调用sparse.

By far the fastest way to generate a sparse matrix wihtin matlab is to load all the values in at once, then generate the sparse matrix in one call to sparse. You have to load the data and arrange it into vectors defining the row and column indices and values for each filled cell. You can then call sparse using the S = sparse(i,j,s,m,n) syntax.

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