在Matlab中向量化数组索引/子集 [英] Vectorizing array indexing/subsetting in Matlab

问题描述

假设我有一个长数据向量y，外加一些索引.我想在每个索引周围提取一个简短的代码段或窗口.

Suppose I have a long data vector y, plus some indices into it. I want to extract a short snippet or window around every index.

例如，假设我要构造一个矩阵，该矩阵包含每个值小于3的之前的64个样本和之后的64个样本.在for循环中这样做很简单:

For example, suppose I want to construct a matrix containing 64 samples before and 64 samples after every value that is below three. This is trivial to do in a for-loop:

WIN_SIZE = 64;

% Sample data with padding
data = [nan(WIN_SIZE,1); randn(1e6,1); nan(WIN_SIZE,1)];

% Sample events, could be anything
index = find(data < 3); 

snippets = nan(length(index), 2*WIN_SIZE + 1);
for ii=1:length(index)
   snippets(ii,:) = data((index(ii)-WIN_SIZE):(index(ii)+WIN_SIZE));
end

但是，这并没有很快.是否有任何方法可以矢量化(或加快)此操作?

However,this is not blazingly fast. Is there any way to vectorize (or otherwise speed up) this operation?

(如果不清楚，索引可以是任何东西，也不一定是数据的属性；我只想简单地说明一下这个想法.)

(In case this is unclear, the index could be anything and may not necessarily be a property of the data; I just wanted something simple to illustrate the idea.)

推荐答案

使用 bsxfun -

snippets = data(bsxfun(@plus,index(:),[-WIN_SIZE:WIN_SIZE]))

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