Matlab函数句柄优化
我在 Matlab 中有一个像这样的函数句柄
fhandle = @(A) max(1-2*A,0).*(2*A.^5+2*A + 1)
其中 < code>A 通常是一个矩阵。我执行了很多次，它减慢了计算速度。可以将其保留为函数句柄（这样我就不必重写代码），但一劳永逸地计算 2*A 然后应用它三次？
提前致谢。
I have a function handle in Matlab like this
fhandle = @(A) max(1-2*A,0).*(2*A.^5+2*A + 1)
Where A is typically a matrix. I perform this quite a few times and it is slowing down the computation. It is possible to keep it as a function handle (so I don't have to rewrite code) but to compute 2*A once and for all and then apply it the three times?
Thanks in advance.
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首先，有一个小问题：您没有计算
2*A3 次。您计算了两次并计算了一次2*A.^5。请注意，幂运算符优先于乘法运算符。您可以将其分解为(2*A).*A.^4，但您可能不会为自己节省太多工作。由于您仅限于 匿名函数 中的单个表达式，在这种情况下，我没有想到特别干净或有效的方法来预先计算
2*A。相反，您可以将乘法因子移到括号之外，以减少执行的乘法量。您可以按如下方式重写方程式：请注意，您的操作使用 MAX将因子 2 移到运算之外不会受到影响，因为它只是将
1-2*A的所有负元素设置为零。从方程的每个部分中删除的因子 2 会导致结果乘以一个因子 4，从而使您执行的逐元素乘法的数量减半。即使您提到不想重写代码，您也可能需要考虑使用 函数 或 子函数 而不是匿名函数。基于 中显示的结果这个关于 OOP 计时问题的答案，看来匿名函数可能有更多的开销。对于这么短的函数，重写它并不需要那么多工作。
First, one small quibble: you're not computing
2*A3 times. You're computing it twice and computing2*A.^5once. Note that power operators take precedence over multiplication operators. You could break it up as(2*A).*A.^4, but you might not be saving yourself much work.Since you are limited to a single expression inside an anonymous function, there are no particularly clean or efficient ways I can think of to precompute
2*Ain this case. Instead, you could just move the multiplicative factors outside the parentheses to reduce the amount of multiplications you perform. You can rewrite your equation as follows:Note that your operation using MAX will be unaffected by moving the factor of 2 outside the operation, since it is simply setting all the negative elements of
1-2*Ato zero. The factors of 2 removed from each part of the equation result in a single factor of 4 multiplying the result, thus halving the number of element-wise multiplications you perform.Even though you mention not wanting to rewrite the code, you might want to consider using a function or subfunction instead of an anonymous function if efficiency is key. Based on the results shown in this answer to a question about OOP timing, it appears that anonymous functions may have more overhead. And for such a short function, rewriting it wouldn't be that much work.