2

下面是一些代码，探索了分配给数组中的单元格（在本例中使用for循环）可能导致的额外复制。

# populate a vector with a million random numbers
n = 10^6
v=runif(n)
# vectorized version: fast
vv<-v*v;
m<-mean(vv); m
# for loop: slow
tracemem(vv)
for(i in 1:length(v)) { vv[i]<-v[i]*v[i] };
m<-mean(vv); m

输出

> vv<-v*v;
> m<-mean(vv); m
[1] 0.3329162
> # for loop: slow
> tracemem(vv)
[1] "<0x000007ffff560010"
> for(i in 1:length(v)) { vv[i]<-v[i]*v[i] };
tracemem[0x000007ffff560010 -> 0x000007fffe570010]: 
> m<-mean(vv); m
[1] 0.3329162

这似乎表明在循环的第一次迭代中存在向量的副本。

注意：这是我之前的问题Why is vectorization faster , this answer to it和this comment on the answer的后续。

只是为了确认复制，我在循环体之外进行了第一次迭代

v=runif(n)
# vectorized version: fast
vv<-v*v;
m<-mean(vv); m
# for loop: slow
tracemem(vv)
vv[1]<-v[1]*v[1]
tracemem(vv)
for(i in 2:length(v)) { vv[i]<-v[i]*v[i] };
m<-mean(vv); m

给出这个输出

> vv<-v*v;
> m<-mean(vv); m
[1] 0.33385
> # for loop: slow
> tracemem(vv)
[1] "<0x000007fffef80010"
> vv[1]<-v[1]*v[1]
tracemem[0x000007fffef80010 -> 0x000007fffddc0010]: 
> tracemem(vv)
[1] "<0x000007fffddc0010"
> for(i in 2:length(v)) { vv[i]<-v[i]*v[i] };
> m<-mean(vv); m
[1] 0.33385 # (different as I generated the random nos again)

在阅读了 joran 的答案和这个 nabble 讨论线程之后，我开始熟悉 R 可能复制向量的想法，例如，当您更改类型如下时

> x = 1:10
> tracemem(x)
[1] "<0x00000000118ba4e0"
> x[5] = 6
tracemem[0x00000000118ba4e0 -> 0x0000000010d03568]: 
> x = 1:10 # starts off as integer
> tracemem(x)
[1] "<0x00000000118ba538"
> x[5] = 6L # setting integer ok
> x[5] = 6 # setting floating point changes type
tracemem[0x00000000118ba538 -> 0x0000000010d03568]: 
> x[6] = 7 # it's now floating point, setting floating point again ok
> x[7] = "asdf" # setting string changes type once more, this tanks on a large array
tracemem[0x0000000010d03568 -> 0x0000000010d03610]:

所以我对发生了什么有一个粗略的了解，但是为什么在我的第一个示例中存在一个副本vv（或者我在解释中犯了什么错误），什么时候vv已经是一个浮点数组？

4

1 回答 1

5

复制是因为 R 认为可能存在对该对象的另一个引用：

x <- 1:10
.Internal(inspect(x))
## @5a27838 13 INTSXP g0c4 [NAM(1)] (len=10, tl=0) 1,2,3,4,5,...
# NAM(1) means that there is one reference to the object.

tracemem(x)
## [1] "<0x05a27838>"
.Internal(inspect(x))
## @5a27838 13 INTSXP g0c4 [NAM(1),TR] (len=10, tl=0) 1,2,3,4,5,...
# Still one reference

mean(x)
## [1] 5.5
.Internal(inspect(x))
## @5a27838 13 INTSXP g0c4 [NAM(2),TR] (len=10, tl=0) 1,2,3,4,5,...
# NAM(2) means "more than one" reference.
# A copy of the "pointer" was taken to pass to "mean", which bumped the count.
# The count starts at (essentially) 1, and is set to 2 if a copy is made.  Never back to 1 though.

x[1] <- 0
tracemem[0x05a27838 -> 0x05a278c8]: 
tracemem[0x05a278c8 -> 0x05a0d6f0]:

分配实际上并不复制数据（直到进行修改）。相反，它会复制指针并指示没有一个是单例：

x <- 1
y <- x
.Internal(inspect(x))
## @5a61848 14 REALSXP g0c1 [NAM(2)] (len=1, tl=0) 1
.Internal(inspect(y))
## @5a61848 14 REALSXP g0c1 [NAM(2)] (len=1, tl=0) 1
y[1] <- 1
.Internal(inspect(y))
## @5a61948 14 REALSXP g0c1 [NAM(1)] (len=1, tl=0) 1
# Note, a new memory address, and NAM(1).
于 2013-06-03T22:36:33.193 回答