查找两个字符变量之间的公共子字符串

I have two character variables (names of objects) and I want to extract the largest common substring.

我有两个字符变量(对象的名称)，我想提取最大的公共子字符串。

a <- c('blahABCfoo', 'blahDEFfoo')
b <- c('XXABC-123', 'XXDEF-123')

I want the following as a result:

我希望得到以下结果:

[1] "ABC" "DEF"

These vectors as input should give the same result:

这些向量作为输入应该得到相同的结果:

a <- c('textABCxx', 'textDEFxx')
b <- c('zzABCblah', 'zzDEFblah')

These examples are representative. The strings contain identifying elements, and the remainder of the text in each vector element is common, but unknown.

这些例子是代表。字符串包含标识元素，每个向量元素中文本的其余部分是通用的，但是未知的。

Is there a solution, in one of the following places (in order of preference):

是否有解决方案，在下列任何一处(按优先次序):

Base R

基地R
Recommended Packages

推荐的包
Packages available on CRAN

包可以在凹口

The answer to the supposed-duplicate does not fulfill these requirements.

假设副本的答案不满足这些要求。

3 个解决方案

#1

Here's a CRAN package for that:

这里有一个CRAN包:

library(qualV)

sapply(seq_along(a), function(i)
    paste(LCS(strsplit(a[i], '')[[1]], strsplit(b[i], '')[[1]])$LCS,
          collapse = ""))

#2

If you dont mind using bioconductor packages, then, You can use Rlibstree. The installation is pretty straightforward.

如果你不介意使用生物导体，那么，你可以使用Rlibstree。安装非常简单。

source("http://bioconductor.org/biocLite.R")
biocLite("Rlibstree")

Then, you can do:

然后,你能做什么:

require(Rlibstree)
ll <- list(a,b)
lapply(data.frame(do.call(rbind, ll), stringsAsFactors=FALSE), 
           function(x) getLongestCommonSubstring(x))

# $X1
# [1] "ABC"

# $X2
# [1] "DEF"

On a side note: I'm not quite sure if Rlibstree uses libstree 0.42 or libstree 0.43. Both libraries are present in the source package. I remember running into a memory leak (and hence an error) on a huge array in perl that was using libstree 0.42. Just a heads up.

附加说明:我不太确定Rlibstree使用了libstree 0.42还是libstree 0.43。这两个库都在源代码包中。我记得在使用libstree 0.42的perl中，遇到了一个内存泄漏(因此出现了一个错误)。只是一个头。

#3

Because I have too many things I don't want to do, I did this instead:

因为我有太多不想做的事情，所以我就这样做了:

Rgames> for(jj in 1:100) {
+ str2<-sample(letters,100,rep=TRUE)
+ str1<-sample(letters,100,rep=TRUE)
+ longs[jj]<-length(lcstring(str1,str2)[[1]])
+ }
Rgames> table(longs)
longs
 2  3  4 
59 39  2

Anyone care to do a statistical estimate of the actual distribution of matching strings? (lcstring is just a brute-force home-rolled function; the output contains all max strings which is why I only look at the first list element)

有人愿意对匹配字符串的实际分布做统计估计吗?(lcstring只是一个蛮力自滚函数;输出包含所有的max字符串，这就是为什么我只看第一个列表元素的原因)

#1