清洁环境以加速 R 中的功能

Question

I have this example data and some example functions

other_data<-c(1,2,3) # data I have to have
fun<-function(a,b,c){
data<-c(a,b,c)
return(data)
} # first function

var_1<-runif(20,10,20) # variables
var_2<-runif(20,10,20)
var_3<-runif(20,10,20)

vars<-data.frame(var_1,var_2,var_3) # data frame of variables
subfun<-function(x){
res<-fun(vars[x,1],vars[x,2],vars[x,3])
return(res)
} # sub function of the first one to use more options and get them into list

final<-lapply(c(1:nrow(vars)),subfun) # this should be the final result I want to get

The problem is, that my real data is much more bigger and I have about 500 "data" (like in first function) which has to be reloaded every time because of different values of a,b,c . And it seems to slow down the function because of memory, ie environment. I don't want to do it like rm(data) and repeat it 500x times in first function before the row return(data) . So my questions

Is there any straightforward way how to remove all objects which was loaded during the function, but only these objects in fun(a,b,c) ? Because I need to DONT remove other_data .

Or more simply, is there straightforward way how to delete all objects like rm(ls(),instead of=c("other_data") ?

Answer 1

If you only want to keep certain object you can use function keep from library gdata. http://www.inside-r.org/packages/cran/gdata/docs/keep

library('gdata')
var1 <- 1
var2 <- 2

ls()
[1] "var1" "var2"

keep(var1, sure = T)    
ls()
[1] "var1"

Setting sure to True performs the removal. Otherwise keep will return names of objects that would have been removed.