R Specify Function Environment

R - Change function environment

If just want the function to be able to get variables from the parent frame or, if not found, from the global environment, this should work (even if I discourage it *) :

g <- function(env=parent.frame()){
  z = get("x",envir=env) + get("y",envir=env) + get("a",envir=env)
  return(z)
}

So, this works :

rm(list=ls(pattern='[^g]')) # to be sure the global env is empty except for g function
a = 2                     

f <- function(){
  x = 1
  y = 1
  return(g())
} 

f()
# returns 4

(*) I discourage this for mainly two reasons:

1. The code is not very readable, and is not immediately clear what g does and where it takes x,y and a.
2. From a functional programming perspective, a good practice is to make functions as "self-contained" as possible (i.e. not relying on external/global variables) and as "stateless" as possible (i.e. not keeping any "state" when called). It's much better to pass what a function needs through its arguments, and let the function be just something that receives an input (through parameters), manipulates it, and returns an output.

Calling an R function in a different environment

Move f into env

environment(f) <- env
f()
# [1] 4

Note: Evaluation of objects across different environments is not desirable, as you have encountered here. It's best to keep all objects that you plan to interact with one another in the same environment.

If you don't want to change the environment of f, you could put all the above into a new function.

fx <- function(f, env) {
    environment(f) <- env
    f()
}
fx(f, env)
# [1] 4

Distinct enclosing environment, function environment, etc. in R

TLDR:

1. indeed, you can change the enclosing environment. Hadley was probably talking about packaged functions.
2. the enclosing and the binding environment. You were correct.
3. that's the execution environment. It only exists for the time the function runs.

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Function environments

You have to distinguish 4 different environments when talking about a function:

• the binding environment is the environment where the function is found (i.e. where its name exists). This is where the actual binding of an object to its name is done. find() gives you the binding environment.
• the enclosing environment is the environment where the function is originally created. This is not necessarily the same as the binding environment (see examples below). environment() gives you the enclosing environment.
• the local environment is the environment within the function. You call that the execution environment.
• the parent frame or calling environment is the environment from where the function was called.

Why does this matter

Every environment has a specific function:

• the binding environment is the environment where you find the function.
• the local environment is the first environment where R looks for objects.
• the general rule is: if R doesn't find an object in the local environment, it then looks in the enclosing environment and so on. The last enclosing environment is always emptyenv().
• the parent frame is where R looks for the value of the objects passed as
  arguments.

You can change the enclosing environment

Indeed, you can change the enclosing environment. It is the enclosing environment of a function from a package you cannot change. In that case you don't change the enclosing environment, you actually create a copy in the new environment:

> ls()
character(0)
> environment(sd)
<environment: namespace:stats>
> environment(sd) <- globalenv()
> environment(sd)
<environment: R_GlobalEnv>
> ls()
[1] "sd"
> find("sd")
[1] ".GlobalEnv"    "package:stats" # two functions sd now
> rm(sd)
> environment(sd)
<environment: namespace:stats>

In this case, the second sd has the global environment as the enclosing and binding environment, but the original sd is still found inside the package environment, and its enclosing environment is still the namespace of that package

The confusion might arise when you do the following:

> f <- sd
> environment(f)
<environment: namespace:stats>
> find("f")
[1] ".GlobalEnv"

What happens here? The enclosing environment is still the namespace ''stats''. That's where the function is created. However, the binding environment is now the global environment. That's where the name "f" is bound to the object.

We can change the enclosing environment to a new environment e. If you check now, the enclosing environment becomes e, but e itself is empty. f is still bound in the global environment.

> e <- new.env()
> e
<environment: 0x000000001852e0a8>
> environment(f) <- e
> find("f")
[1] ".GlobalEnv"
> environment(f)
<environment: 0x000000001852e0a8>
> ls(e)
character(0)

The enclosing environment of e is the global environment. So f still works as if its enclosure was the global environment. The environment e is enclosed in it, so if something isn't found in e, the function looks in the global environment and so on.

But because e is an environment, R calls that a parent environment.

> parent.env(e)
<environment: R_GlobalEnv>
> f(1:3)
[1] 1 

Namespaces and package environments

This principle is also the "trick" packages use:

• the function is created in the namespace. This is an environment that is enclosed by the namespaces of other imported packages, and eventually the global environment.
• the binding for the function is created in the package environment. This is an environment that encloses the global environment and possible other packages.

The reason for this is simple: objects can only be found inside the environment you are in, or in its enclosing environments.

• a function must be able to find other functions(objects), so the local environment must be enclosed by possibly the namespaces of other packages it imports, the base package and lastly the global environment.
• a function must be findable from within the global environment. Hence the binding (i.e. the name of the function) must be in an environment that is enclosed by the global environment. This is the package environment (NOT the namespace!)

An illustration:

Now suppose you make an environment with the empty environment as a parent. If you use this as an enclosing environment for a function, nothing works any longer. Because now you circumvent all the package environments, so you can't find a single function any more.

> orphan <- new.env(parent = emptyenv())
> environment(f) <- orphan
> f(1:3)
Error in sqrt(var(if (is.vector(x) || is.factor(x)) x else as.double(x),  : 
  could not find function "sqrt"

The parent frame

This is where it gets interesting. The parent frame or calling environment, is the environment where the values passed as arguments are looked up. But that parent frame can be the local environment of another function. In this case R looks first in that local environment of that other function, and then in the enclosing environment of the calling function, and so all the way up to the global environment, the environments of the attached packages until it reaches the empty environment. That's where the "object not found" bug sleeps.

How to use the R environment and the globalenv() function

Your card deck is stored in a vector deck in your Global Environment.

deal <- function(){
  card <- deck[1,]
  assign("deck", deck[-1,], envir = globalenv())
  card
}

Each function call creates it's own environment, an object assigned inside a function "lives" just inside of it. That's why you don't "see" a vector named card in your Global Environment (unless you created one before, but this vector is uneffected by deal functions card <- deck[1,] statement).

So assign("deck", deck[-1]) (without the envir argument) would be the same as

deal <- function(){
  card <- deck[1,]
  deck <- deck[-1,]
  card
}

but this won't change your deck outside the function. The vector deck inside the function just exists inside the function. To change the deck outside the function, you have to tell R where to change it. So that's why assign("deck", deck[-1,], envir = globalenv()) is used.

So let's start over with your function deal:

card <- deck[1,]

assigns the first element of deck to card. But wait! deck doesn't exists inside the function? So how is this possible? If the object isn't found inside the function, R looks one level up, in your case most likely the Global Environment. So there R finds an object/vector named deck and does the assignment. Now we have an object/vector named card that exists inside the function.

For further understanding, take a look at Chapter 6: Functions in Advanced R.

Set a functions environment to that of the calling environment (parent.frame) from within function

Well, a function cannot change it's default environment, but you can use eval to run code in a different environment. I'm not sure this exactly qualifies as elegant, but this should work:

helpFunction<-function(){
    eval(quote(importantVar1+1), parent.frame())
}

mainFunction<-function(importantVar1){
    return(helpFunction())
}

mainFunction(importantVar1=3)

How can I reference the local environment within a function, in R?

To get the current environment, just call environment().

In general, sys.frame returns any of the environments currently on the call stack, and sys.nframe returns the current depth of the call stack. sys.frames returns a list of all environments on the call stack.

environment(f) returns the closure environment for a function f (where it will look for functions and global variables).

parent.env(e) returns the parent environment where it will look if a symbol is not found in e.

f <- function() {
  function() list(curEnv=environment(), parent=parent.env(environment()), 
          grandParent=parent.env(parent.env(environment())), callStack=sys.frames(), 
          callStackDepth=sys.nframe())
}
g <- function(f, n=2) if (n>2) g(f, n-1) else f()

floc <- f() # generate a local function
g(floc, 3) # call it

This will call the local function floc with a stack depth of 3. It returns a list with the current environment, it's parent (the local environment in f), and it's grand parent (where f was defined, so globalenv). It also returns the list of stack frames (environments). These are the environments for the recursive calls in g (except the last one which is the current environment of floc).

Why doesn't R look up for the specified object in the provided envrionment parents tree?

So, this is an unusually nuanced issue. There are two relevant types of environments that you need to think about here, the binding environment, or the environment that has a binding to your function, and the enclosing environment, or the environment where your function was created. In this case the binding environment is e10, but the enclosing environment is the global environment. From Hadley Wickham's Advanced R:

The enclosing environment belongs to the function, and never changes, even if the function is moved to a different environment. The enclosing environment determines how the function finds values; the binding environments determine how we find the function.

Consider the following (executed after executing your supplied code) that demonstrates this:

eval(expression(testfun()), envir = e10)
# [1] "e10"
# Error in testfun() : object 'testvar' not found
testvar <- 600
eval(expression(testfun()), envir = e10)
# [1] "e10"
# [1] 600

Moreover, now consider:

eval(envir = e10, expr = expression(
    testfun2 <- function(x) {
        print(envnames::environment_name(caller_env()))
        return (testvar)
    }
))
eval(expression(testfun2()), envir = e10)
# [1] "e10"
# [1] 1200

I hope this clarifies the issue.

Update: Determining the Enclosing and Binding Environments

So how can we determine the binding and enclosing environments for functions such as testfun()?

As G. Grothendieck's answer shows, the environment() function gives you the enclosing environment for a function:

environment(e10$testfun)
# <environment: R_GlobalEnv>

To my knowledge, there isn't a simple function in base R to give you a function's binding environments. If the function you're looking for is in a parent environment, you can use pryr::where():

pryr::where("mean")
# <environment: base>

(There is a base function to see if a function is in an environment, exists(), and pryr::where() uses it. But, it doesn't recurse through parent environments like where().)

However, if you're having to search through child environments, to my knowledge there isn't a function for that. But, seems pretty simple to mock one up:

get_binding_environments <- function(fname) {
    ## First we need to find all the child environments to search through.
    ## We don't want to start from the execution environment;
    ## we probably want to start from the calling environment,
    ## but you may want to change this to the global environment.
    e <- parent.frame()
    ## We want to get all of the environments we've created
    objects <- mget(ls(envir = e), envir = e)
    environments <- objects[sapply(objects, is.environment)]
    ## Then we use exists() to see if the function has a binding in any of them
    contains_f <- sapply(environments, function(E) exists(fname, where = E))
    return(unique(environments[contains_f]))
}

get_binding_environments("testfun")
# [[1]]
# <environment: 0x55f865406518>

e10
# <environment: 0x55f865406518>

Is it possible to set a function's environment while runtime in R?

With this code you get exactly what you're looking for:

subfun0 <- function() {
    e <- parent.frame()
    attr(e, "name") <- "my_env"
    assign("my_env", 1,
                 envir = parent.frame(),
                 inherits = FALSE, immediate = TRUE)
    return(NULL)
}

subsubfun <- function() {
    print("  subsubfun")
    print("  =========")
    print(exists("my_env"))
    print(exists("my_env", parent.frame()))
    print(exists("my_env", parent.frame(2)))
    return(NULL)
}

subfun <- function() {
    print(" subfun")
    print(" ======")
    print(exists("my_env"))
    print(exists("my_env", parent.frame()))
    print(exists("my_env", parent.frame(2)))
    subsubfun()
    return(NULL)
}

fun1 <- function() {
    print("fun1")
    print("====")
    subfun0()
    print(exists("my_env"))
    print(exists("my_env", parent.frame()))
    print(exists("my_env", parent.frame(2)))
    subfun()
    return(NULL)
}

fun1()

[1] "fun1"
[1] "===="
[1] TRUE
[1] FALSE
[1] FALSE
[1] " subfun"
[1] " ======"
[1] FALSE
[1] TRUE
[1] FALSE
[1] "  subsubfun"
[1] "  ========="
[1] FALSE
[1] FALSE
[1] TRUE
NULL

The point is that: parent.frame(2) is not equal to parent.env(parent.frame())

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