更快地应用 `all` 函数的方法?
Faster way of applying `all` function?
假设我有一个逻辑数组:
dimensions = c(10,100,200,300)
x = runif(prod(dimensions))>0.3
dim(x) = dimensions
有没有更快的方法得到结果:
y = colMeans(apply(x,2:4,all))
?
应用很慢,这个用例很简单,所以我徘徊...
使用colSums
:
system.time(
y <- colMeans(apply(x,2:4,all))
)
# user system elapsed
#6.916 0.058 6.978
system.time(
z <- colMeans(colSums(x, dims = 1) == dim(x)[1])
)
# user system elapsed
#0.117 0.000 0.117
identical(y, z)
#[1] TRUE
假设我有一个逻辑数组:
dimensions = c(10,100,200,300)
x = runif(prod(dimensions))>0.3
dim(x) = dimensions
有没有更快的方法得到结果:
y = colMeans(apply(x,2:4,all))
?
应用很慢,这个用例很简单,所以我徘徊...
使用colSums
:
system.time(
y <- colMeans(apply(x,2:4,all))
)
# user system elapsed
#6.916 0.058 6.978
system.time(
z <- colMeans(colSums(x, dims = 1) == dim(x)[1])
)
# user system elapsed
#0.117 0.000 0.117
identical(y, z)
#[1] TRUE