在R中查找对象的组合

Question

I have the following example code:

library(caTools)
sample1 = rnorm(20)
sample2 = rnorm(30)
sample3 = rnorm(40)
# could be more samples

args = list(sample1, sample2, sample3) # could be more

> combs(c(args), k=2)
     [,1]       [,2]      
[1,] Numeric,20 Numeric,30
[2,] Numeric,20 Numeric,40
[3,] Numeric,30 Numeric,40

However, this is not what is desired. I would like to feed combs input that should give the same as:

> combs(c("sample1","sample2", "sample3"),k=2)
     [,1]      [,2]     
[1,] "sample1" "sample2"
[2,] "sample1" "sample3"
[3,] "sample2" "sample3"

and from there I would want to use get to extract the vectors for each sampleX object by row.

How can I do this without hardcoding "sample1", "sample2", etc. so that I can have as many as samples as are fed to it?

Answer 1

From library(gtools) :

combinations(3,2,c("sample1","sample2", "sample3"))

Result:

     [,1]      [,2]     
[1,] "sample1" "sample2"
[2,] "sample1" "sample3"
[3,] "sample2" "sample3"

The same result can be obtained if those objects are named elements of a list:

tmp <- list(sample1=1:3,sample2=4:6,sample3=7:9)
combinations(3,2,names(tmp))

Or, if those objects are all in an environment:

tmp <- new.env()
tmp$sample1 <- 1:3
tmp$sample2 <- 4:6
tmp$sample3 <- 7:9
combinations(3,2,objects(tmp))

Answer 2

How about this? I use simplified data as an illustrative example.

Edit

Thanks to @GSee for recommending two improvements in this approach [see comment].

This is not something I'd be keen to do, but we use ls and the pattern argument on the names of all objects in your global environment to return the names of those that fit the pattern ie all objects which include "sample" in the object names - so be careful - and then stick them in a list using mget .

We then get the combinations of list elements using combn and use an anonymous function to combine all elements of list pairs using expand.grid . If you want this as a two column data.frame you can use do.call and rbind the returned list together:

sample1 <- 1:2
sample2 <- 3:4
sample3 <- 5:6

args <-mget( ls( pattern = "^sample\\d+") , env = .GlobalEnv )

res <- combn( length(args) , 2 , FUN = function(x) expand.grid(args[[x[1]]] , args[[x[2]]]) , simplify = FALSE )

do.call( rbind , res )
   Var1 Var2
1     1    3
2     2    3
3     1    4
4     2    4
5     1    5
6     2    5
7     1    6
8     2    6
9     3    5
10    4    5
11    3    6
12    4    6

Answer 3

Here is an approach

# put samples in separate structure, for instance a list
samples <- list(s1=rnorm(20), s2=rnorm(30), s3=rnorm(40))     

cmb <- t(combn(names(samples),m=2))
apply(cmb,1,FUN=function(x) list(samples[[x[[1]]]], samples[[x[[2]]]]))