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I am trying to update a global list from inside a function.
Here is the code that does not work (can be sourced as a whole file):
require(rlang)
(my_list <- list(a = 1, b = "two", c = "set outside"))
print( paste("my_list$c is" , my_list$c) )
my_function <- function(x = 1, y = 2, parent_object_name = "my_list") {
z <- x + y # do some stuff (irrelevant here)
some_names <- "updated inside"
upper_env_object_name <- paste0(parent_object_name, "$c")
# browser()
# env_poke(env = env_tail(), upper_env_object_name, some_names) # does not work
# env_poke(env = env_parents()[[1]], upper_env_object_name, some_names) # does not work
env_poke(env = caller_env(), upper_env_object_name, some_names ) # creates `my_list$c` character vector
# force(env_poke(env = caller_env(), upper_env_object_name, some_names )) # creates `my_list$c` character vector
# browser()
# env_poke(env = caller_env(), paste0("as.list(",upper_env_object_name,")"), some_names) # creates as.list(my_list$c)` character vector
return(z)
}
my_function(x = 1, y = 2, parent_object_name = "my_list")
print(class(`my_list$c`))
print( `my_list$c`)
print( paste("my_list$c is" , my_list$c) )
I found this but it does not help:
Updating a nested list object in the global environment from within a function in R
Tried also with assign, and specifying the environment.
Background: I have some S3- subclases and want to keep track of them in the parent class object, which is also a list. The subclass objects are created "on-demand" and I want to have an overview what was created. My workaround for now is to create a new vector in the global environment and update it with :
if (exists("global_names_list")) global_names_list <<- unique(rbind(global_names_list, some_names)) else global_names_list <<- some_names
Modify List in Global Environment
Subscript the environment like this:
f <- function(listname = "my_list", envir = .GlobalEnv) {
envir[[listname]]$c <- "some value"
}
# test
my_list <- list(a = 1, b = "two", c = "set outside")
f()
str(my_list)
## List of 3
## $ a: num 1
## $ b: chr "two"
## $ c: chr "some value"
Functional Approach
Note that working via side effects such as the code above is not the usual style used in R. Rather an object oriented style using Reference Classes or other object oriented framework or a functional style is more common. For the functional style here is an example:
g <- function(x) modifyList(x, list(c = "somevalue"))
# test
my_list <- list(a = 1, b = "two", c = "set outside")
my_list <- g(my_list)
str(my_list)
## List of 3
## $ a: num 1
## $ b: chr "two"
## $ c: chr "somevalue"
Example of object oriented processing
Regarding the background paragraph at the end of the question here is an example of where we have a top object that contains properties a and last (both numeric) and a method add. There are any number of sub-objects that have property 'b' and inherit the add method to add a in top to b in the current object. last is the value of the last sum that was calculated by any sub-object.
library(proto)
top <- proto(a = 1,
last = NULL,
add = function(.) { top$last <- .$a + .$b; .$last }
)
sub1 <- top$proto(b = 2)
sub1$add()
# [1] 3
top$last
# [1] 3
sub2 <- top$proto(b = 3)
sub2$add()
# [1] 4
top$last
# [1] 4
This is probably not the best way, but it is a way:
my_list <- list(a = 1, b = "two", c = "set outside")
my_function <- function(x = 1, y = 2, parent_object_name = "my_list"){
z <- x+y
some_names <- "updated inside"
lst <- get(parent_object_name)
lst$c <- some_names
assign(parent_object_name, lst, envir = .GlobalEnv)
return(z)
}
my_function()
#> [1] 3
#check
my_list
#> $a
#> [1] 1
#>
#> $b
#> [1] "two"
#>
#> $c
#> [1] "updated inside"
Given an arbitrarily nested list, how can I find if a list contains empty lists? Consider the following example:
mylist <- list(list("foo", "bar", "baz", list(list())))
I tried rapply, but that skips through lists. While I could use lapply, I'd need to know the level of nesting beforehand. For this exercise, I don't need to know where the list is (although that would be a bonus), I just need a way to detect if there is one.
What about a function like this
has_empty_list <- function(x) {
if(is.list(x)) {
if (length(x)==0) {
return(TRUE)
} else {
return(any(vapply(x, has_empty_list, logical(1))))
}
} else {
return(FALSE)
}
}
Basically we create a recursive function to look for lists of length 0.
has_empty_list( list(list("foo", "bar", "baz", list(list()))) )
# TRUE
has_empty_list( list(list("foo", "bar", "baz", list(list(4)))) )
# FALSE
And here's a modification to find the index of the empty list
find_empty_list <- function(x, index=c()) {
if(is.list(x)) {
#list
if (length(x)==0) {
if (length(index)==0) {
return(0)
} else {
return(index)
}
} else {
m <- Map(find_empty_list, x, lapply(seq_along(x), function(i) append(index,i)))
# return the most deeply nested
return( m[[which.max(lengths(m))]] )
}
} else {
return(numeric())
}
}
This should return a vector of the index that you can use to find the empty list. For example
( i <- find_empty_list(mylist) )
# [1] 1 4 1
mylist[[i]]
# list()
If the first parameter itself is an empty list, it will return 0
find_empty_list(list())
# 0
and if there is no empty list, it should return an empty vector
find_empty_list(list(1:3, list("c", a~b)))
# numeric()
Another convenient option to work with nested list is to use data.tree package:
library(data.tree)
nodes <- as.Node(mylist)
any(node$Get(function(node) length(as.list(node))) == 0)
# [1] TRUE
Another approach is to use rrapply in the rrapply-package (an extension of base-rrapply):
library(rrapply)
## check if any empty list exists
any(
rrapply(mylist,
classes = "list",
condition = function(x) length(x) < 1,
f = function(x) TRUE,
deflt = FALSE,
how = "unlist"
)
)
#> [1] TRUE
It is straightforward to update the above call to return the index vectors of any empty lists:
## return flat list with position vectors of empty list
rrapply(mylist,
classes = "list",
condition = function(x) length(x) < 1,
f = function(x, .xpos) .xpos,
how = "flatten"
)
#> [[1]]
#> [1] 1 4 1
Here, we make use of the .xpos argument which evaluates to the position of the current list element under evaluation.
Note that this automatically returns all empty list positions instead of only one:
mylist2 <- list(list("foo", list(), "baz", list(list())))
rrapply(mylist2,
classes = "list",
condition = function(x) length(x) < 1,
f = function(x, .xpos) .xpos,
how = "flatten"
)
#> [[1]]
#> [1] 1 2
#>
#> [[2]]
#> [1] 1 4 1
## using MrFlick's find_empty_list function
find_empty_list(mylist2)
#> [1] 1 4 1
I want to create a string in a loop and use this string as object in this loop. Here is a simplified example:
for (i in 1:2) {
x <- paste("varname",i, sep="")
x <- value
}
the loop should create varname1, varname2. Then I want to use varname1, varname2 as objects to assign values. I tried paste(), print() etc.
Thanks for help!
You could create the call() to <- and then evaluate it. Here's an example,
value <- 1:5
for (i in 1:2) {
x <- paste("varname",i, sep="")
eval(call("<-", as.name(x), value))
}
which creates the two objects varname1 and varname2
varname1
# [1] 1 2 3 4 5
varname2
# [1] 1 2 3 4 5
But you should really try to avoid assigning to the global environment from with in a method/function. We could use a list along with substitute() and then we have the new variables together in the same place.
f <- function(aa, bb) {
eval(substitute(a <- b, list(a = as.name(aa), b = bb)))
}
Map(f, paste0("varname", 1:2), list(1:3, 3:6))
# $varname1
# [1] 1 2 3
#
# $varname2
# [1] 3 4 5 6
assign("variableName", 5)
would do that.
For example if you have variable names in array of strings you can set them in loop as:
assign(varname[1], 2 + 2)
More and more information
https://stat.ethz.ch/R-manual/R-patched/library/base/html/assign.html
#MahmutAliÖZKURAN has answered your question about how to do this using a loop. A more "R-ish" way to accomplish this might be:
mapply(assign, <vector of variable names>, <vector of values>,
MoreArgs = list(envir = .GlobalEnv))
Or, as in the case you specified above:
mapply(assign, paste0("varname", 1:2), <vector of values>,
MoreArgs = list(envir = .GlobalEnv))
I had the same issue and for some reason my apply's weren't working (lapply, assign directly, or my preferred goto, mclapply)
But this worked
vectorXTS <- mclapply(symbolstring,function(x)
{
df <- symbol_data_set[symbol_data_set$Symbol==x,]
return(xts(as.data.frame(df[,-1:-2]),order.by=as.POSIXct(df$Date)))
})
names(symbolstring) <- symbolstring
names(vectorXTS) <- symbolstring
for(i in symbolstring) assign(symbolstring[i],vectorXTS[i])
I want to assign multiple variables in a single line in R. Is it possible to do something like this?
values # initialize some vector of values
(a, b) = values[c(2,4)] # assign a and b to values at 2 and 4 indices of 'values'
Typically I want to assign about 5-6 variables in a single line, instead of having multiple lines. Is there an alternative?
I put together an R package zeallot to tackle this very problem. zeallot includes an operator (%<-%) for unpacking, multiple, and destructuring assignment. The LHS of the assignment expression is built using calls to c(). The RHS of the assignment expression may be any expression which returns or is a vector, list, nested list, data frame, character string, date object, or custom objects (assuming there is a destructure implementation).
Here is the initial question reworked using zeallot (latest version, 0.0.5).
library(zeallot)
values <- c(1, 2, 3, 4) # initialize a vector of values
c(a, b) %<-% values[c(2, 4)] # assign `a` and `b`
a
#[1] 2
b
#[1] 4
For more examples and information one can check out the package vignette.
There is a great answer on the Struggling Through Problems Blog
This is taken from there, with very minor modifications.
USING THE FOLLOWING THREE FUNCTIONS
(Plus one for allowing for lists of different sizes)
# Generic form
'%=%' = function(l, r, ...) UseMethod('%=%')
# Binary Operator
'%=%.lbunch' = function(l, r, ...) {
Envir = as.environment(-1)
if (length(r) > length(l))
warning("RHS has more args than LHS. Only first", length(l), "used.")
if (length(l) > length(r)) {
warning("LHS has more args than RHS. RHS will be repeated.")
r <- extendToMatch(r, l)
}
for (II in 1:length(l)) {
do.call('<-', list(l[[II]], r[[II]]), envir=Envir)
}
}
# Used if LHS is larger than RHS
extendToMatch <- function(source, destin) {
s <- length(source)
d <- length(destin)
# Assume that destin is a length when it is a single number and source is not
if(d==1 && s>1 && !is.null(as.numeric(destin)))
d <- destin
dif <- d - s
if (dif > 0) {
source <- rep(source, ceiling(d/s))[1:d]
}
return (source)
}
# Grouping the left hand side
g = function(...) {
List = as.list(substitute(list(...)))[-1L]
class(List) = 'lbunch'
return(List)
}
Then to execute:
Group the left hand side using the new function g()
The right hand side should be a vector or a list
Use the newly-created binary operator %=%
# Example Call; Note the use of g() AND `%=%`
# Right-hand side can be a list or vector
g(a, b, c) %=% list("hello", 123, list("apples, oranges"))
g(d, e, f) %=% 101:103
# Results:
> a
[1] "hello"
> b
[1] 123
> c
[[1]]
[1] "apples, oranges"
> d
[1] 101
> e
[1] 102
> f
[1] 103
Example using lists of different sizes:
Longer Left Hand Side
g(x, y, z) %=% list("first", "second")
# Warning message:
# In `%=%.lbunch`(g(x, y, z), list("first", "second")) :
# LHS has more args than RHS. RHS will be repeated.
> x
[1] "first"
> y
[1] "second"
> z
[1] "first"
Longer Right Hand Side
g(j, k) %=% list("first", "second", "third")
# Warning message:
# In `%=%.lbunch`(g(j, k), list("first", "second", "third")) :
# RHS has more args than LHS. Only first2used.
> j
[1] "first"
> k
[1] "second"
Consider using functionality included in base R.
For instance, create a 1 row dataframe (say V) and initialize your variables in it. Now you can assign to multiple variables at once V[,c("a", "b")] <- values[c(2, 4)], call each one by name (V$a), or use many of them at the same time (values[c(5, 6)] <- V[,c("a", "b")]).
If you get lazy and don't want to go around calling variables from the dataframe, you could attach(V) (though I personally don't ever do it).
# Initialize values
values <- 1:100
# V for variables
V <- data.frame(a=NA, b=NA, c=NA, d=NA, e=NA)
# Assign elements from a vector
V[, c("a", "b", "e")] = values[c(2,4, 8)]
# Also other class
V[, "d"] <- "R"
# Use your variables
V$a
V$b
V$c # OOps, NA
V$d
V$e
here is my idea. Probably the syntax is quite simple:
`%tin%` <- function(x, y) {
mapply(assign, as.character(substitute(x)[-1]), y,
MoreArgs = list(envir = parent.frame()))
invisible()
}
c(a, b) %tin% c(1, 2)
gives like this:
> a
Error: object 'a' not found
> b
Error: object 'b' not found
> c(a, b) %tin% c(1, 2)
> a
[1] 1
> b
[1] 2
this is not well tested though.
A potentially dangerous (in as much as using assign is risky) option would be to Vectorize assign:
assignVec <- Vectorize("assign",c("x","value"))
#.GlobalEnv is probably not what one wants in general; see below.
assignVec(c('a','b'),c(0,4),envir = .GlobalEnv)
a b
0 4
> b
[1] 4
> a
[1] 0
Or I suppose you could vectorize it yourself manually with your own function using mapply that maybe uses a sensible default for the envir argument. For instance, Vectorize will return a function with the same environment properties of assign, which in this case is namespace:base, or you could just set envir = parent.env(environment(assignVec)).
As others explained, there doesn't seem to be anything built in. ...but you could design a vassign function as follows:
vassign <- function(..., values, envir=parent.frame()) {
vars <- as.character(substitute(...()))
values <- rep(values, length.out=length(vars))
for(i in seq_along(vars)) {
assign(vars[[i]], values[[i]], envir)
}
}
# Then test it
vals <- 11:14
vassign(aa,bb,cc,dd, values=vals)
cc # 13
One thing to consider though is how to handle the cases where you e.g. specify 3 variables and 5 values or the other way around. Here I simply repeat (or truncate) the values to be of the same length as the variables. Maybe a warning would be prudent. But it allows the following:
vassign(aa,bb,cc,dd, values=0)
cc # 0
list2env(setNames(as.list(rep(2,5)), letters[1:5]), .GlobalEnv)
Served my purpose, i.e., assigning five 2s into first five letters.
Had a similar problem recently and here was my try using purrr::walk2
purrr::walk2(letters,1:26,assign,envir =parent.frame())
https://stat.ethz.ch/R-manual/R-devel/library/base/html/list2env.html:
list2env(
list(
a=1,
b=2:4,
c=rpois(10,10),
d=gl(3,4,LETTERS[9:11])
),
envir=.GlobalEnv
)
If your only requirement is to have a single line of code, then how about:
> a<-values[2]; b<-values[4]
I'm afraid that elegent solution you are looking for (like c(a, b) = c(2, 4)) unfortunatelly does not exist. But don't give up, I'm not sure! The nearest solution I can think of is this one:
attach(data.frame(a = 2, b = 4))
or if you are bothered with warnings, switch them off:
attach(data.frame(a = 2, b = 4), warn = F)
But I suppose you're not satisfied with this solution, I wouldn't be either...
R> values = c(1,2,3,4)
R> a <- values[2]; b <- values[3]; c <- values[4]
R> a
[1] 2
R> b
[1] 3
R> c
[1] 4
Another version with recursion:
let <- function(..., env = parent.frame()) {
f <- function(x, ..., i = 1) {
if(is.null(substitute(...))){
if(length(x) == 1)
x <- rep(x, i - 1);
stopifnot(length(x) == i - 1)
return(x);
}
val <- f(..., i = i + 1);
assign(deparse(substitute(x)), val[[i]], env = env);
return(val)
}
f(...)
}
example:
> let(a, b, 4:10)
[1] 4 5 6 7 8 9 10
> a
[1] 4
> b
[1] 5
> let(c, d, e, f, c(4, 3, 2, 1))
[1] 4 3 2 1
> c
[1] 4
> f
[1] 1
My version:
let <- function(x, value) {
mapply(
assign,
as.character(substitute(x)[-1]),
value,
MoreArgs = list(envir = parent.frame()))
invisible()
}
example:
> let(c(x, y), 1:2 + 3)
> x
[1] 4
> y
[1]
Combining some of the answers given here + a little bit of salt, how about this solution:
assignVec <- Vectorize("assign", c("x", "value"))
`%<<-%` <- function(x, value) invisible(assignVec(x, value, envir = .GlobalEnv))
c("a", "b") %<<-% c(2, 4)
a
## [1] 2
b
## [1] 4
I used this to add the R section here: http://rosettacode.org/wiki/Sort_three_variables#R
Caveat: It only works for assigning global variables (like <<-). If there is a better, more general solution, pls. tell me in the comments.
For a named list, use
list2env(mylist, environment())
For instance:
mylist <- list(foo = 1, bar = 2)
list2env(mylist, environment())
will add foo = 1, bar = 2 to the current environement, and override any object with those names. This is equivalent to
mylist <- list(foo = 1, bar = 2)
foo <- mylist$foo
bar <- mylist$bar
This works in a function, too:
f <- function(mylist) {
list2env(mylist, environment())
foo * bar
}
mylist <- list(foo = 1, bar = 2)
f(mylist)
However, it is good practice to name the elements you want to include in the current environment, lest you override another object... and so write preferrably
list2env(mylist[c("foo", "bar")], environment())
Finally, if you want different names for the new imported objects, write:
list2env(`names<-`(mylist[c"foo", "bar"]), c("foo2", "bar2")), environment())
which is equivalent to
foo2 <- mylist$foo
bar2 <- mylist$bar
I want to assign multiple variables in a single line in R. Is it possible to do something like this?
values # initialize some vector of values
(a, b) = values[c(2,4)] # assign a and b to values at 2 and 4 indices of 'values'
Typically I want to assign about 5-6 variables in a single line, instead of having multiple lines. Is there an alternative?
I put together an R package zeallot to tackle this very problem. zeallot includes an operator (%<-%) for unpacking, multiple, and destructuring assignment. The LHS of the assignment expression is built using calls to c(). The RHS of the assignment expression may be any expression which returns or is a vector, list, nested list, data frame, character string, date object, or custom objects (assuming there is a destructure implementation).
Here is the initial question reworked using zeallot (latest version, 0.0.5).
library(zeallot)
values <- c(1, 2, 3, 4) # initialize a vector of values
c(a, b) %<-% values[c(2, 4)] # assign `a` and `b`
a
#[1] 2
b
#[1] 4
For more examples and information one can check out the package vignette.
There is a great answer on the Struggling Through Problems Blog
This is taken from there, with very minor modifications.
USING THE FOLLOWING THREE FUNCTIONS
(Plus one for allowing for lists of different sizes)
# Generic form
'%=%' = function(l, r, ...) UseMethod('%=%')
# Binary Operator
'%=%.lbunch' = function(l, r, ...) {
Envir = as.environment(-1)
if (length(r) > length(l))
warning("RHS has more args than LHS. Only first", length(l), "used.")
if (length(l) > length(r)) {
warning("LHS has more args than RHS. RHS will be repeated.")
r <- extendToMatch(r, l)
}
for (II in 1:length(l)) {
do.call('<-', list(l[[II]], r[[II]]), envir=Envir)
}
}
# Used if LHS is larger than RHS
extendToMatch <- function(source, destin) {
s <- length(source)
d <- length(destin)
# Assume that destin is a length when it is a single number and source is not
if(d==1 && s>1 && !is.null(as.numeric(destin)))
d <- destin
dif <- d - s
if (dif > 0) {
source <- rep(source, ceiling(d/s))[1:d]
}
return (source)
}
# Grouping the left hand side
g = function(...) {
List = as.list(substitute(list(...)))[-1L]
class(List) = 'lbunch'
return(List)
}
Then to execute:
Group the left hand side using the new function g()
The right hand side should be a vector or a list
Use the newly-created binary operator %=%
# Example Call; Note the use of g() AND `%=%`
# Right-hand side can be a list or vector
g(a, b, c) %=% list("hello", 123, list("apples, oranges"))
g(d, e, f) %=% 101:103
# Results:
> a
[1] "hello"
> b
[1] 123
> c
[[1]]
[1] "apples, oranges"
> d
[1] 101
> e
[1] 102
> f
[1] 103
Example using lists of different sizes:
Longer Left Hand Side
g(x, y, z) %=% list("first", "second")
# Warning message:
# In `%=%.lbunch`(g(x, y, z), list("first", "second")) :
# LHS has more args than RHS. RHS will be repeated.
> x
[1] "first"
> y
[1] "second"
> z
[1] "first"
Longer Right Hand Side
g(j, k) %=% list("first", "second", "third")
# Warning message:
# In `%=%.lbunch`(g(j, k), list("first", "second", "third")) :
# RHS has more args than LHS. Only first2used.
> j
[1] "first"
> k
[1] "second"
Consider using functionality included in base R.
For instance, create a 1 row dataframe (say V) and initialize your variables in it. Now you can assign to multiple variables at once V[,c("a", "b")] <- values[c(2, 4)], call each one by name (V$a), or use many of them at the same time (values[c(5, 6)] <- V[,c("a", "b")]).
If you get lazy and don't want to go around calling variables from the dataframe, you could attach(V) (though I personally don't ever do it).
# Initialize values
values <- 1:100
# V for variables
V <- data.frame(a=NA, b=NA, c=NA, d=NA, e=NA)
# Assign elements from a vector
V[, c("a", "b", "e")] = values[c(2,4, 8)]
# Also other class
V[, "d"] <- "R"
# Use your variables
V$a
V$b
V$c # OOps, NA
V$d
V$e
here is my idea. Probably the syntax is quite simple:
`%tin%` <- function(x, y) {
mapply(assign, as.character(substitute(x)[-1]), y,
MoreArgs = list(envir = parent.frame()))
invisible()
}
c(a, b) %tin% c(1, 2)
gives like this:
> a
Error: object 'a' not found
> b
Error: object 'b' not found
> c(a, b) %tin% c(1, 2)
> a
[1] 1
> b
[1] 2
this is not well tested though.
A potentially dangerous (in as much as using assign is risky) option would be to Vectorize assign:
assignVec <- Vectorize("assign",c("x","value"))
#.GlobalEnv is probably not what one wants in general; see below.
assignVec(c('a','b'),c(0,4),envir = .GlobalEnv)
a b
0 4
> b
[1] 4
> a
[1] 0
Or I suppose you could vectorize it yourself manually with your own function using mapply that maybe uses a sensible default for the envir argument. For instance, Vectorize will return a function with the same environment properties of assign, which in this case is namespace:base, or you could just set envir = parent.env(environment(assignVec)).
As others explained, there doesn't seem to be anything built in. ...but you could design a vassign function as follows:
vassign <- function(..., values, envir=parent.frame()) {
vars <- as.character(substitute(...()))
values <- rep(values, length.out=length(vars))
for(i in seq_along(vars)) {
assign(vars[[i]], values[[i]], envir)
}
}
# Then test it
vals <- 11:14
vassign(aa,bb,cc,dd, values=vals)
cc # 13
One thing to consider though is how to handle the cases where you e.g. specify 3 variables and 5 values or the other way around. Here I simply repeat (or truncate) the values to be of the same length as the variables. Maybe a warning would be prudent. But it allows the following:
vassign(aa,bb,cc,dd, values=0)
cc # 0
list2env(setNames(as.list(rep(2,5)), letters[1:5]), .GlobalEnv)
Served my purpose, i.e., assigning five 2s into first five letters.
Had a similar problem recently and here was my try using purrr::walk2
purrr::walk2(letters,1:26,assign,envir =parent.frame())
https://stat.ethz.ch/R-manual/R-devel/library/base/html/list2env.html:
list2env(
list(
a=1,
b=2:4,
c=rpois(10,10),
d=gl(3,4,LETTERS[9:11])
),
envir=.GlobalEnv
)
If your only requirement is to have a single line of code, then how about:
> a<-values[2]; b<-values[4]
I'm afraid that elegent solution you are looking for (like c(a, b) = c(2, 4)) unfortunatelly does not exist. But don't give up, I'm not sure! The nearest solution I can think of is this one:
attach(data.frame(a = 2, b = 4))
or if you are bothered with warnings, switch them off:
attach(data.frame(a = 2, b = 4), warn = F)
But I suppose you're not satisfied with this solution, I wouldn't be either...
R> values = c(1,2,3,4)
R> a <- values[2]; b <- values[3]; c <- values[4]
R> a
[1] 2
R> b
[1] 3
R> c
[1] 4
Another version with recursion:
let <- function(..., env = parent.frame()) {
f <- function(x, ..., i = 1) {
if(is.null(substitute(...))){
if(length(x) == 1)
x <- rep(x, i - 1);
stopifnot(length(x) == i - 1)
return(x);
}
val <- f(..., i = i + 1);
assign(deparse(substitute(x)), val[[i]], env = env);
return(val)
}
f(...)
}
example:
> let(a, b, 4:10)
[1] 4 5 6 7 8 9 10
> a
[1] 4
> b
[1] 5
> let(c, d, e, f, c(4, 3, 2, 1))
[1] 4 3 2 1
> c
[1] 4
> f
[1] 1
My version:
let <- function(x, value) {
mapply(
assign,
as.character(substitute(x)[-1]),
value,
MoreArgs = list(envir = parent.frame()))
invisible()
}
example:
> let(c(x, y), 1:2 + 3)
> x
[1] 4
> y
[1]
Combining some of the answers given here + a little bit of salt, how about this solution:
assignVec <- Vectorize("assign", c("x", "value"))
`%<<-%` <- function(x, value) invisible(assignVec(x, value, envir = .GlobalEnv))
c("a", "b") %<<-% c(2, 4)
a
## [1] 2
b
## [1] 4
I used this to add the R section here: http://rosettacode.org/wiki/Sort_three_variables#R
Caveat: It only works for assigning global variables (like <<-). If there is a better, more general solution, pls. tell me in the comments.
For a named list, use
list2env(mylist, environment())
For instance:
mylist <- list(foo = 1, bar = 2)
list2env(mylist, environment())
will add foo = 1, bar = 2 to the current environement, and override any object with those names. This is equivalent to
mylist <- list(foo = 1, bar = 2)
foo <- mylist$foo
bar <- mylist$bar
This works in a function, too:
f <- function(mylist) {
list2env(mylist, environment())
foo * bar
}
mylist <- list(foo = 1, bar = 2)
f(mylist)
However, it is good practice to name the elements you want to include in the current environment, lest you override another object... and so write preferrably
list2env(mylist[c("foo", "bar")], environment())
Finally, if you want different names for the new imported objects, write:
list2env(`names<-`(mylist[c"foo", "bar"]), c("foo2", "bar2")), environment())
which is equivalent to
foo2 <- mylist$foo
bar2 <- mylist$bar