I would like to implement a generic function:
call_with_parameters <- function(func, parameters) {
call func with parameters and return result
}
that calls the given function func (given as paramter) with a list of parameters, so func must not be able to cope with generic parameters (like ...). As return the call
For example to call: mean(x=1:4, na.rm=TRUE) as
call_with_parameters(mean, list(x=1:4, na.rm=TRUE))
Any suggestions?
I think, you are looking for do.call for the construction of function calls.
The function constructs the call and evaluates it immediately( You can also use call to construct the call and evaluates it later using eval for example). do.call takes the arguments
from an object of mode "list" containing all the arguments of function to be evaluated. For example:
do.call("mean", list(x=1:4,na.rm=TRUE))
is equivalent to :
mean(x=1:4,na.rm=TRUE)
Related
I read a question on function arguments which included the formals function and I was eager to find out how the function is defined. I used base:::formals and it gives:
function (fun = sys.function(sys.parent()))
{
if (is.character(fun))
fun <- get(fun, mode = "function", envir = parent.frame())
.Internal(formals(fun))
}
To me it is unclear how this works because inside the definition of the formals function the formals function is used. That seems paradox to me.
.Internal(formals(fun)) calls an internal R function, coded in C. It just happens that this C internal function is also named formals.
So it does not call the same function, just an internal one that happens to be internally named "formals".
cf https://stat.ethz.ch/R-manual/R-devel/library/base/html/Internal.html
I have a question on Java 8 Functional Programming. I am trying to achieve something using functional programming, and need some guidance on how to do it.
My requirement is to wrap every method execution inside timer function which times the method execution. Here's the example of timer function and 2 functions I need to time.
timerMethod(String timerName, Function func){
timer.start(timerName)
func.apply()
timer.stop()
}
functionA(String arg1, String arg2)
functionB(int arg1, intArg2, String ...arg3)
I am trying to pass functionA & functionB to timerMethod, but functionA & functionB expects different number & type of arguments for execution.
Any ideas how can I achieve it.
Thanks !!
you should separate it into two things by Separation of Concerns to make your code easy to use and maintaining. one is timing, another is invoking, for example:
// v--- invoking occurs in request-time
R1 result1 = timerMethod("functionA", () -> functionA("foo", "bar"));
R2 result2 = timerMethod("functionB", () -> functionB(1, 2, "foo", "bar"));
// the timerMethod only calculate the timing-cost
<T> T timerMethod(String timerName, Supplier<T> func) {
timer.start(timerName);
try {
return func.get();
} finally {
timer.stop();
}
}
IF you want to return a functional interface rather than the result of that method, you can done it as below:
Supplier<R1> timingFunctionA =timerMethod("A", ()-> functionA("foo", "bar"));
Supplier<R2> timingFunctionB =timerMethod("B", ()-> functionB(1, 2, "foo", "bar"));
<T> Supplier<T> timerMethod(String timerName, Supplier<T> func) {
// v--- calculate the timing-cost when the wrapper function is invoked
return () -> {
timer.start(timerName);
try {
return func.get();
} finally {
timer.stop();
}
};
}
Notes
IF the return type of all of your functions is void, you can replacing Supplier with Runnable and then make the timerMethod's return type to void & remove return keyword from timerMethod.
IF some of your functions will be throws a checked exception, you can replacing Supplier with Callable & invoke Callable#call instead.
Don't hold onto the arguments and then pass them at the last moment. Pass them immediately, but delay calling the function by wrapping it with another function:
Producer<?> f1 =
() -> functionA(arg1, arg2);
Producer<?> f2 =
() -> functionB(arg1, arg2, arg3);
Here, I'm wrapping each function call in a lambda (() ->...) that takes 0 arguments. Then, just call them later with no arguments:
f1()
f2()
This forms a closure over the arguments that you supplied in the lambda, which allows you to use the variables later, even though normally they would have been GC'd for going out of scope.
Note, I have a ? as the type of the Producer since I don't know what type your functions return. Change the ? to the return type of each function.
Introduction
The other answers show how to use a closure to capture the arguments of your function, no matter its number. This is a nice approach and it's very useful, if you know the arguments in advance, so that they can be captured.
Here I'd like to show two other approaches that don't require you to know the arguments in advance...
If you think it in an abstract way, there are no such things as functions with multiple arguments. Functions either receive one set of values (aka a tuple), or they receive one single argument and return another function that receives another single argument, which in turn returns another one-argument function that returns... etc, with the last function of the sequence returning an actual result (aka currying).
Methods in Java might have multiple arguments, though. So the challenge is to build functions that always receive one single argument (either by means of tuples or currying), but that actually invoke methods that receive multiple arguments.
Approach #1: Tuples
So the first approach is to use a Tuple helper class and have your function receive one tuple, either a Tuple2 or Tuple3:
So, the functionA of your example might receive one single Tuple2<String, String> as an argument:
Function<Tuple2<String, String>, SomeReturnType> functionA = tuple ->
functionA(tuple.getFirst(), tuple.getSecond());
And you could invoke it as follows:
SomeReturnType resultA = functionA.apply(Tuple2.of("a", "b"));
Now, in order to decorate the functionA with your timerMethod method, you'd need to do a few modifications:
static <T, R> Function<T, R> timerMethod(
String timerName,
Function<? super T, ? extends R> func){
return t -> {
timer.start(timerName);
R result = func.apply(t);
timer.stop();
return result;
};
}
Please note that you should use a try/finally block to make your code more robust, as shown in holi-java's answer.
Here's how you might use your timerMethod method for functionA:
Function<Tuple2<String, String>, SomeReturnType> timedFunctionA = timerMethod(
"timerA",
tuple -> functionA(tuple.getFirst(), tuple.getSecond());
And you can invoke timedFunctionA as any other function, passing it the arguments now, at invocation time:
SomeReturnType resultA = timedFunctionA.apply(Tuple2.of("a", "b"));
You can take a similar approach with the functionB of your example, except that you'd need to use a Tuple3<Integer, Integer, String[]> for the argument (taking care of the varargs arguments).
The downside of this approach is that you need to create many Tuple classes, i.e. Tuple2, Tuple3, Tuple4, etc, because Java lacks built-in support for tuples.
Approach #2: Currying
The other approach is to use a technique called currying, i.e. functions that accept one single argument and return another function that accepts another single argument, etc, with the last function of the sequence returning the actual result.
Here's how to create a currified function for your 2-argument method functionA:
Function<String, Function<String, SomeReturnType>> currifiedFunctionA =
arg1 -> arg2 -> functionA(arg1, arg2);
Invoke it as follows:
SomeReturnType result = currifiedFunctionA.apply("a").apply("b");
If you want to decorate currifiedFunctionA with the timerMethod method defined above, you can do as follows:
Function<String, Function<String, SomeReturnType>> timedCurrifiedFunctionA =
arg1 -> timerMethod("timerCurryA", arg2 -> functionA(arg1, arg2));
Then, invoke timedCurrifiedFunctionA exactly as you'd do with any currified function:
SomeReturnType result = timedCurrifiedFunctionA.apply("a").apply("b");
Please note that you only need to decorate the last function of the sequence, i.e. the one that makes the actual call to the method, which is what we want to measure.
For the method functionB of your example, you can take a similar approach, except that the type of the currified function would now be:
Function<Integer, Function<Integer, Function<String[], SomeResultType>>>
which is quite cumbersome, to say the least. So this is the downside of currified functions in Java: the syntax to express their type. On the other hand, currified functions are very handy to work with and allow you to apply several functional programming techniques without needing to write helper classes.
I would like to write a function where one of the argument is a function written by the user.
Specifically, I have something like:
My_function(n,g){
x<-dnorm(n,0,1)
y<-g(x)
return(y)
}
For example, g(x)=x^2 ... but is chosen by the user. Of course, I could directly put g(dnorm(n,0,1)) as argument but I would like the user to write it in terms of x, i.e. g<-x^2 in the example.
How could I do this since the x object is only defined within the function (and not in the arguments)
I can't define the g function beforehand (otherwise, I reckon it's easy). It has to be defined within "My_function" so that the user defines everything he needs in one line.
Why not just declare g as a function with argument?
g=function(x) x^2
My_function=function(n,g){
x<-dnorm(n,0,1)
y<-g(x)
return(y)
}
My_function(1,g)
I'm writing some functions in R and I'm having some issues. Summarizing, inside the function I'm writing, I call another function that I've developed. The 2nd function shares some arguments with the first, how to specify to this 2nd function that has to take the same values for its arguments that the ones in the first function?
first.fx=function(arg1,arg2,arg3,...){
.
.
.
second.fx=function(arg2,arg3,arg4,...){
}
}
The second.fx shares with the first arg2 & arg3. How to inherit these to values to second.fx?
Simply assign the values (which come from the call to first.fx as default parameters in the definition of second.fx:
second.fx <- function(arg2=arg2,arg3=arg3,arg4,...){
You don't need to declare the arguments explicitly in the definition of second.fx. By the magic of lexical scoping, these variables will be found in second.fx's enclosing environment, which is that of first.fx.
first.fx <- function(arg1, arg2, arg3, ...)
{
second.fx <- function(arg4)
{
# values of arg2/3 will be found from first.fx's environment
}
}
I'm trying to figure out how to get R's callCC function for short-circuiting evalutation of a function to work with functions like lapply and Reduce.
Motivation
This would make Reduce and and lapply have asymptotic efficiency > O(n), by allowing you to
exit a computation early.
For example, if I'm searching for a value in a list I could map a 'finder' function across the list, and the second it is found lapply stops running and that value is returned (much like breaking a loop, or using a return statement to break out early).
The problem is I am having trouble writing the functions that lapply and Reduce should take using a style that callCC requires.
Example
Say I'm trying to write a function to find the value '100' in a list: something equivalent to
imperativeVersion <- function (xs) {
for (val in xs) if (val == 100) return (val)
}
The function to pass to lapply would look like:
find100 <- function (val) { if (val == 100) SHORT_CIRCUIT(val) }
functionalVersion <- function (xs) lapply(xs, find100)
This (obviously) crashes, since the short circuiting function hasn't been defined yet.
callCC( function (SHORT_CIRCUIT) lapply(1:1000, find100) )
The problem is that this also crashes, because the short circuiting function wasn't around when find100 was defined. I would like for something similar to this to work.
the following works because SHORT_CIRCUIT IS defined at the time that the function passed to lapply is created.
callCC(
function (SHORT_CIRCUIT) {
lapply(1:1000, function (val) {
if (val == 100) SHORT_CIRCUIT(val)
})
)
How can I make SHORT_CIRCUIT be defined in the function passed to lapply without defining it inline like above?
I'm aware this example can be achieved using loops, reduce or any other number of ways. I am looking for a solution to the problem of using callCC with lapply and Reduce in specific.
If I was vague or any clarification is needed please leave a comment below. I hope someone can help with this :)
Edit One:
The approach should be 'production-quality'; no deparsing functions or similar black magic.
I found a soluton to this problem:
find100 <- function (val) {
if (val == 100) SHORT_CIRCUIT(val)
}
short_map <- function (fn, coll) {
callCC(function (SHORT_CIRCUIT) {
clone_env <- new.env(parent = environment(fn))
clone_env$SHORT_CIRCUIT <- SHORT_CIRCUIT
environment(fn) <- clone_env
lapply(coll, fn)
})
}
short_map(find100, c(1,2,100,3))
The trick to making higher-order functions work with callCC is to assign the short-circuiting function into the input functions environment before carrying on with the rest of the program. I made a clone of the environment to avoid unintended side-effects.
You can achieve this using metaprogramming in R.
#alexis_laz's approach was in fact already metaprogramming.
However, he used strings which are a dirty hack and error prone. So you did well to reject it.
The correct way to approach #alexis_laz's approach would be by wrangling on code level. In base R this is done using substitute(). There are however better packages e.g. rlang by Hadley Wickham. But I give you a base R solution (less dependency).
lapply_ <- function(lst, FUN) {
eval.parent(
substitute(
callCC(function(return_) {
lapply(lst_, FUN_)
}),
list(lst_ = lst, FUN_=substitute(FUN))))
}
Your SHORT_CIRCUIT function is actually a more general, control flow return function (or a break function which takes an argument to return it). Thus, I call it return_.
We want to have a lapply_ function, in which we can in the FUN= part use a return_ to break out of the usual lapply().
As you showed, this is the aim:
callCC(
function (return_) {
lapply(1:1000, function (x) if (x == 100) return_(x))
}
)
Just with the problem, that we want to be able to generalize this expression.
We want
callCC(
function(return_) lapply(lst, FUN_)
)
Where we can use inside the function definition we give for FUN_ the return_.
We can let, however, the function defintion see return_ only if we insert the function definition code into this expression.
This exactly #alexis_laz tried using string and eval.
Or you did this by manipulating environment variables.
We can safely achieve the insertion of literal code using substitute(expr, replacer_list) where expr is the code to be manipulated and replacer_list is the lookup table for the replacement of code.
By substitute(FUN) we take the literal code given for FUN= for lapply_ without evaluating it. This expression returns literal quoted code (better than the string in #alexis_laz's approach).
The big substitute command says: "Take the expression callCC(function(return_) lapply(lst_, FUN_)) and replace lst_ in this expression by the list given for coll and FUN_ by the literal quoted expression given for FUN.
This replaced expression is then evaluated in the parent environment (eval.parent()) meaning: the resulting expression replaces the lapply_() call and is executed exactly where it was placed.
Such use of eval.parent() (or eval( ... , envir=parent.frame())) is fool proof. (otherwise, tidyverse packages wouldn't be production level ...).
So in this way, you can generalize callCC() calls.
lapply_(1:1000, FUN=function(x) if (x==100) return_(x))
## [1] 100
I don't know if it can be of use, but:
find100 <- "function (val) { if (val == 100) SHORT_CIRCUIT(val) }"
callCC( function (SHORT_CIRCUIT) lapply(1:1000, eval(parse(text = find100))) )
#[1] 100