使用copy()或sapply()重复用户定义的函数 [英] Repeating a user-defined function using replicate() or sapply()
问题描述
我已经定义了一个自定义函数,如下所示:
I have defined a custom function, like this:
my.fun = function() {
for (i in 1:1000) {
...
for (j in 1:20) {
...
}
}
return(output)
}
返回由1000行和20列组成的输出矩阵output
.
which returns an output matrix, output
, composed by 1000 rows and 20 columns.
我需要做的是重复执行该函数5次,并将五个output
结果存储到一个全新的矩阵中,例如final
,但不使用另一个for循环 (这是为了使代码更清晰,也因为稍后我想尝试并行化这5个重复).
What I need to do is to repeat the function say 5 times and to store the five output
results into a brand new matrix, say final
, but without using another for-loop (this for making the code clearer, and also because in a second moment I would like to try to parallelize these additional 5 repetitions).
因此,final
应该是具有5000行和20列的矩阵(这5次重复的原理是,在我使用的两个for循环中,除其他功能外,sample
).
Hence final
should be a matrix with 5000 rows and 20 columns (the rationale behind these 5 repetitions is that within the two for-loops I use, among other functions, sample
).
我尝试使用final <- replicate(5, my.fun())
,它可以正确地计算五个重复项,但是随后我必须手动"将元素放入全新的5000 x 20矩阵中. (也许使用sapply()
?).非常感谢
I tried to use final <- replicate(5, my.fun())
, which correctly computes the five replications, but then I have to "manually" put the elements into a brand new 5000 x 20 matrix.. is there a more elgant way to do so? (maybe using sapply()
?). Many thanks
推荐答案
按原样,您可能有一个具有三个维度的数组.如果您想要一个列表,则可以添加simple = FALSE.试试这个:
As is stands you probably have an array with three dimensions. If you wanted to have a list you would have added simplify=FALSE. Try this:
do.call( rbind, replicate(5, my.fun(), simplify=FALSE ) )
或者在最终"仍然是数组的情况下可以使用aperm
:
Or you can use aperm
in the case where "final" is still an array:
fun <- function() matrix(1:10, 2,5)
final <- replicate( 2, fun() )
> final
, , 1
[,1] [,2] [,3] [,4] [,5]
[1,] 1 3 5 7 9
[2,] 2 4 6 8 10
, , 2
[,1] [,2] [,3] [,4] [,5]
[1,] 1 3 5 7 9
[2,] 2 4 6 8 10
> t( matrix(aperm(final, c(2,1,3)), 5,4) )
[,1] [,2] [,3] [,4] [,5]
[1,] 1 3 5 7 9
[2,] 2 4 6 8 10
[3,] 1 3 5 7 9
[4,] 2 4 6 8 10
可能会有更经济的矩阵运算.我只是还没有发现.
There may be more economical matrix operations. I just haven't discovered one yet.
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