避免R中的循环 [英] Avoiding loops in R

问题描述

我决定学习R.我试图了解如何编写"R风格"函数，并避免循环.这是一个示例情况:

I have decided to learn R. I am trying to get a sense of how to write "R style" functions and to avoid looping. Here is a sample situation:

给定一个向量a，我想计算一个向量b，其元素b[i](向量索引从1开始)定义如下:

Given a vector a, I would like to compute a vector b whose elements b[i] (the vector index begins at 1) are defined as follows:

1 <= i <= 4:
b[i] = NaN

5 <= i <= length(a):
b[i] = mean(a[i-4] to a[i])

基本上，如果我们假装"a"是一个速度列表，其中第一个条目在时间= 0，第二个条目在时间= 1秒，第三个条目在时间= 2秒...我想获得一个表示过去5秒内平均速度的相应向量.

Essentially, if we pretend 'a' is a list of speeds where the first entry is at time = 0, the second at time = 1 second, the third at time = 2 seconds... I would like to obtain a corresponding vector describing the average speed over the past 5 seconds.

例如: 如果a is (1,1,1,1,1,4,6,3,6,8,9)，则b应该是(NaN, NaN, NaN, NaN, 1, 1.6, 2.6, 3, 4, 5.4, 6.4)

E.g.: If a is (1,1,1,1,1,4,6,3,6,8,9) then b should be (NaN, NaN, NaN, NaN, 1, 1.6, 2.6, 3, 4, 5.4, 6.4)

我可以使用循环来执行此操作，但是我觉得这样做不是"R风格".

I could do this using a loop, but I feel that doing so would not be in "R style".

谢谢

Tungata

推荐答案

由于这些滚动功能通常适用于时间序列数据，因此一些更新和更丰富的时间序列数据处理软件包已经为您做到了:

Because these rolling functions often apply with time-series data, some of the newer and richer time-series data-handling packages already do that for you:

R> library(zoo)   ## load zoo
R> speed <- c(1,1,1,1,1,4,6,3,6,8,9)
R> zsp <- zoo( speed, order.by=1:length(speed) )  ## creates a zoo object
R> rollmean(zsp, 5)                               ## default use
  3   4   5   6   7   8   9 
1.0 1.6 2.6 3.0 4.0 5.4 6.4 
R> rollmean(zsp, 5, na.pad=TRUE, align="right")   ## with padding and aligned
  1   2   3   4   5   6   7   8   9  10  11 
 NA  NA  NA  NA 1.0 1.6 2.6 3.0 4.0 5.4 6.4 
R> 

zoo 具有出色的文档，它将向您展示更多示例，特别是如何使用真实(可能是不规则)日期执行此操作； xts 对此进行了进一步扩展，但

The zoo has excellent documentation that will show you many, many more examples, in particular how to do this with real (and possibly irregular) dates; xts extends this further but zoo is a better starting point.

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