命令A(〜A)在matlab中实际上是做什么的 [英] What does the command A(~A) really do in matlab

问题描述

我一直在寻找找到矩阵非零极小值的最有效方法，并在论坛上找到它:

I was looking to find the most efficient way to find the non zero minimum of a matrix and found this on a forum :

让数据成为矩阵A.

A(~A) = nan;
minNonZero = min(A);

这是非常简短和有效的(至少在代码行数上)，但是我不明白在执行此操作时会发生什么.我找不到关于此的任何文档，因为它不是像+，-，\这样的矩阵上的operation.

This is very short and efficient (at least in number of code lines) but I don't understand what happens when we do this. I can't find any documentation about this since it's not an operation on matrices like +,-,\,... would be.

有人可以给我解释一下还是给我链接，或者可以帮助我了解完成的事情吗? 谢谢 ！

Could anyone explain me or give me a link or something that could help me understand what is done ? Thank you !

推荐答案

它使用 ~是not运算符.当在双精度数组上使用时，它将查找所有等于零的元素.例如:

~ in Matlab is the not operator. When used on a double array, it finds all elements equal to zero. e.g.:

~[0 3 4 0]

逻辑矩阵中的结果

[1 0 0 1]

即这是找到所有零元素的快速方法

i.e. it's a quick way to find all the zero elements

因此，如果A = [0 3 4 0]，则~A = [1 0 0 1]，因此现在A(~A) = A([1 0 0 1]). A([1 0 0 1])使用逻辑索引仅影响正确的元素，因此在本例中为元素1和元素4.

So if A = [0 3 4 0] then ~A = [1 0 0 1] so now A(~A) = A([1 0 0 1]). A([1 0 0 1]) uses logical indexing to only affect the elements that are true so in this case element 1 and element 4.

最后，A(~A) = NaN将用NaN替换A中等于0的所有元素，而min忽略该元素，从而找到最小的非零元素.

Finally A(~A) = NaN will replace all the elements in A that were equal to 0 with NaN which min ignores and thus you find the smallest non-zero element.

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