2017-05-31 35 views
3

給定一個向量v <- c(1, 10, 22)和一個固定的自然數說c <- 3如何擴展v整數在一個大小爲c的窗口中。因此,載體將成爲w(即1膨脹三個整數到每一側,整數-2,-1,0,1,2,3,4):用常數展開數值向量元素(自然數)

> w 
[1] -2 -1 0 1 2 3 4 7 8 9 10 11 12 13 19 20 21 22 23 24 25 
+1

'C(T(sapply (-3:3,'+ \',v)))' –

回答

2

我們可以使用sapply

c(sapply(v, function(x) (x-c):(x+c))) 
#[1] -2 -1 0 1 2 3 4 7 8 9 10 11 12 13 19 20 21 22 23 24 25 

或者Map

unlist(Map(`:`, v-c, v+c)) 
+1

這真是太棒了,簡潔。在第二,你應用函數':'兩個參數(我的範圍的限制)? – user3375672

+1

@ user3375672'Map'從矢量'vc'和'v + c'中獲取相應的元素,並將其提供給':'以獲取序列 – akrun

2

使用mapply

c(mapply(seq, v-c, v+c)) 

#[1] -2 -1 0 1 2 3 4 7 8 9 10 11 12 13 19 20 21 22 23 24 25 
5

另一種方法是

c(t(sapply(-c:c, `+`, v))) 
#[1] -2 -1 0 1 2 3 4 7 8 9 10 11 12 13 19 20 21 22 23 24 25 

這是大V向量因爲sapply循環迭代只在-c:c代替v每個元素更有效。一個簡單的比較表明這一點:

set.seed(1) 
v <- sample(1e6) 
system.time(unlist(Map(`:`, v-c, v+c)))    # akrun 1 
#  User  System verstrichen 
#  1.518  0.067  1.595 
system.time(c(sapply(v, function(x) (x-c):(x+c)))) # akrun 2 
#  User  System verstrichen 
#  1.564  0.074  1.652 
system.time(c(t(sapply(-c:c, '+', v))))    # docendo 
#  User  System verstrichen 
#  0.082  0.024  0.106 
system.time(c(mapply(seq, v-c, v+c)))     # 989 
#  User  System verstrichen 
#  7.132  0.123  7.292 
+0

這更快:'unlist(lapply(-c:c,'+ ',v))' – digEmAll

+1

@digEmAll,true,但不是爲了順序,否則你不會在我的方法中需要't' –

+0

哦,是的,你是對的 – digEmAll

1

這裏還有一個非常快的選項(可能不是很優雅,但...):

w <- rep.int(v, rep(c*2+1,length(v))) + (-c:c) 

基準:

library(microbenchmark) 
set.seed(1) 
v <- sample(1e6) 

c <- 3 
microbenchmark(times=30, 
       docendo =c(t(sapply(-c:c, '+', v))), 
       digemall=rep.int(v, rep(c*2+1,length(v))) + (-c:c) 
) 
# Unit: milliseconds 
#  expr  min  lq  mean median  uq  max neval 
# docendo 81.04337 82.50133 100.7718 83.78972 99.89731 169.38202 30 
# digemall 28.57355 30.28533 37.0091 31.01103 32.18491 90.90412 30 

c <- 20 
microbenchmark(times=30, 
       docendo =c(t(sapply(-c:c, '+', v))), 
       digemall=rep.int(v, rep(c*2+1,length(v))) + (-c:c) 
) 
# Unit: milliseconds 
#  expr  min  lq  mean median  uq  max neval 
# docendo 581.9529 626.4765 673.2964 663.0599 713.8367 787.1848 30 
# digemall 174.3748 177.2943 198.9419 180.0702 200.0904 319.6669 30