[英]Get runs of consecutive integers of certain length and sample from first values
I am trying to create a function that will return the first integer of a subset of a vector such that the values of the subset are discrete, increasing by 1, and of a specified length.我正在尝试创建一个 function ,它将返回向量子集的第一个 integer ,使得子集的值是离散的,增加 1 并且具有指定的长度。
For example, using the input data 'v' and a specified length 'l' of 3:例如,使用输入数据 'v' 和指定长度 'l' 为 3:
v <- c(3, 4, 5, 6, 15, 16, 25, 26, 27)
l <- 3
The possible sub-vectors of consecutive values of length 3 would be:长度为 3 的连续值的可能子向量为:
c(3, 4, 5)
c(4, 5, 6)
c(25, 26, 27)
Then I want to randomly choose one of these vectors and return the first/lowest number, ie 3, 4, or 25.然后我想随机选择其中一个向量并返回第一个/最小的数字,即 3、4 或 25。
Here's an approach with base R
:这是使用基础
R
的方法:
First, we create all possible sub-vectors of length length
.首先,我们创建所有可能的长度为
length
的子向量。 Next, we subset that list of vectors based on the cumsum
of their difference equalling 1
.接下来,我们根据等于
1
的差值的cumsum
向量列表进行子集化。 The is.na
test ensures the last vectors which contain NA
are also filtered out. is.na
测试确保最后包含NA
的向量也被过滤掉。 Then we just bind the remaining vectors into a matrix and sample the first column.然后我们只需将剩余的向量绑定到一个矩阵中并对第一列进行采样。
SampleSequencialVectors <- function(vec, length){
all.vecs <- lapply(seq_along(vec),function(x)vec[x:(x+(length-1))])
seq.vec <- all.vecs[sapply(all.vecs,function(x) all(diff(x) == 1 & !is.na(diff(x))))]
sample(do.call(rbind,seq.vec)[,1],1)
}
replicate(10, SampleSequencialVectors(v, 3))
# [1] 3 4 3 3 4 4 25 25 3 25
Or if you prefer a tidyverse type approach:或者,如果您更喜欢 tidyverse 类型的方法:
SampleSequencialVectorsPurrr <- function(vec, length){
vec %>%
seq_along %>%
purrr::map(~vec[.x:(.x+(length-1))]) %>%
purrr::keep(~ all(diff(.x) == 1 & !is.na(diff(.x)))) %>%
purrr::invoke(rbind,.) %>%
{sample(.[,1],size = 1)}
}
replicate(10, SampleSequencialVectorsPurrr(v, 3))
[1] 4 25 25 3 25 4 4 3 4 25
split(v, cumsum(c(1L, diff(v) != 1)))
split(v, cumsum(c(1L, diff(v) != 1)))
runs[lengths(runs) >= lim]
runs[lengths(runs) >= lim]
x[1:(length(x) - lim + 1)]
).x[1:(length(x) - lim + 1)]
)。 From all possible first values, sample 1.从所有可能的第一个值中,样本 1。
runs = split(v, cumsum(c(1L, diff(v),= 1))) first = lapply(runs[lengths(runs) >= lim]: function(x) x[1,(length(x) - lim + 1)]) sample(unlist(first), 1)
Here we loop over runs of sufficient length, and not all individual values (see the other answers), thus it may be faster on larger vectors (haven't tested).在这里,我们循环遍历足够长度的运行,而不是所有单个值(请参阅其他答案),因此它可能在较大的向量上更快(尚未测试)。
Slightly more compact using data.table
:使用
data.table
稍微更紧凑:
sample(data.table(v)[ , if(.N >= 3) v[1:(length(v) - lim + 1)],
by = .(cumsum(c(1L, diff(v) != 1)))]$V1, 1)
*Credits to the nice canonical: How to split a vector into groups of consecutive sequences? *归功于nice canonical: 如何将向量拆分为连续序列组? .
.
Base R two lines: Please note this solution assumes v is sorted.基本 R 两行:请注意此解决方案假定 v 已排序。
consec_seq <- sapply(seq_along(v), function(i)split(v, abs(v - v[i]) > 1)[1])
consec_seq[lengths(consec_seq) == l][sample.int(l, 1)]
As a reusable function (not assuming sorted v):作为可重复使用的 function(不假设已排序 v):
conseq_split_sample <- function(vec, n){
v <- sort(vec)
consec_seq <- sapply(seq_along(v), function(i)split(v, abs(v - v[i]) > 1)["FALSE"])
consec_seq[lengths(consec_seq) == n][sample.int(n, 1)]
}
conseq_split_sample(v, l)
Data:数据:
l <- 3
v <- c(3, 4, 5, 6, 15, 16, 25, 26, 27)
Tooting my own horn -- cgwtools::seqle
is like rle
but you can specify the desired increment in a run.吹响我自己的号角
cgwtools::seqle
rle
rle 类似,但您可以在运行中指定所需的增量。 seqle(x, incr = 0,..)
is the same as rle(x)
seqle(x, incr = 0,..)
与rle(x)
相同
Then just grab the run lengths and starting values from the result.然后从结果中获取运行长度和起始值。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.