I want to use quoted arguments in my function and I would like to allow the user to specify that they don't want to use the argument by setting it to NULL. However, rlang::ensym throws an error when it receives a NULL argument. Here is my code:
f <- function(var){
rlang::ensym(var)
return(var + 2)
}
# This works
variable = 2
f(variable)
# This throws an error
f(NULL)
The error message is:
Error: Only strings can be converted to symbols
I already tried adding an if-clause with is.null(var) before the expression with rlang::ensym, but of course, this doesn't work as the variable is not yet quoted at this time.
How can I check that the supplied quoted variable is NULL in order to handle it differently?
If you need to allow for NULL, it's more robust to use quosures first. Then you can inspect the quosure to see what's inside. For example
f <- function(var){
var <- rlang::enquo(var)
if (rlang::quo_is_null(var)) {
var <- NULL
} else if (rlang::quo_is_symbol(var)) {
var <- rlang::get_expr(var)
} else {
stop(paste("Expected symbol but found", class(rlang::get_expr(var))))
}
return(var)
}
And that returns
f(variable)
# variable
f(NULL)
# NULL
f(x+1)
# Error in f(x + 1) : Expected symbol but found call
Or you can use whatever logic is appropriate for your actual requirements.
Related
How can a function inspect and modify the arguments of a call that it received as argument?
Application: A user feeds a call to function a as an argument to function b, but they forget to specify one of the required arguments of a. How can function b detect the problem and fix it?
In this minimal example, function a requires two arguments:
a <- function(arg1, arg2) {
return(arg1 + arg2)
}
Function b accepts a call and an argument. The commented lines indicate what I need to do:
b <- function(CALL, arg3) {
# 1. check if `arg2` is missing from CALL
# 2. if `arg2` is missing, plug `arg3` in its place
# 3. return evaluated call
CALL
}
Expected behavior:
b(CALL = a(arg1 = 1, arg2 = 2), arg3 = 3)
> 3
b(CALL = a(arg1 = 1), arg3 = 3)
> 4
The second call currently fails because the user forgot to specify the required arg2 argument. How can function b fix this mistake automatically?
Can I exploit lazy evaluation to modify the call to a before it is evaluated? I looked into rlang::modify_call but couldn't figure it out.
Here's a method that would work
b <- function(CALL, arg3) {
scall <- substitute(CALL)
stopifnot(is.call(scall)) #check that it's a call
lcall <- as.list(scall)
if (!"arg2" %in% names(lcall)) {
lcall <- c(lcall, list(arg2 = arg3))
}
eval.parent(as.call(lcall))
}
We use substitute() to grab the unevaluated version the CALL parameter. We convert it to a list so we can modify it. Then we append to the list another list with the parameter name/value we want. Finally, we turn the list back into a call and then evaluate that call in the environment of the caller rather than in the function body itself.
If you wanted to use rlang::modify_call and other rlang functions you could use
b <- function(CALL, arg3) {
scall <- rlang::enquo(CALL)
stopifnot(rlang::quo_is_call(scall))
if (!"arg2" %in% names(rlang::quo_get_expr(scall))) {
scall <- rlang::call_modify(scall, arg2=arg3)
}
rlang::eval_tidy(scall, env = rlang::caller_env())
}
I don't see why fancy language manipulation is needed. The problem is what to do when a, which requires 2 arguments, is supplied only 1. Wrapping it with b, which has a default value for the 2nd argument, solves this.
b <- function(arg1, arg2=42)
{
a(arg1, arg2)
}
b(1)
# [1] 43
b(1, 2)
# [1] 3
I am trying to make a function which gets few inputs. I would like to know how to check the availability of my arguments . Here is my function:
MyFunction<-function(data,window,dim,option) {
}
First, I want to see if there is any argument , if no, print an error
is it correct to use
if ~nargin
error('no input data')
}
Then, I want to make sure that the second argument is also inserted
is it right to ask like this
if nargin < 2
error('no window size specified')
}
Then, I want to check if the third argument is empty , set it as 1
if nargin < 3 || isempty(dim)
dim<-1
}
you can use hasArg()
testfunction <- function(x,y){
if(!hasArg(x)){
stop("missing x")
}
if(!hasArg(y)){
y = 3
}
return(x+y)
}
>testfunction(y=2)
Error in testfunction(y = 2) : missing x
> testfunction(x=1,y=2)
[1] 3
> testfunction(x=1)
[1] 4
As #Ben Bolker said , missing is used to test whether a value was specified as an argument to a function. You can have different conditions in your R functions such as warning or stop.
In your case, I would do the following
MyFunction<-function(data,window,dim,option) {
if (missing(data))
stop("the first argument called data is missing")
if (missing(window))
stop("the second argument called window is missing")
if (missing(dim))
dim <- 1
if (missing(option))
stop("the second argument called option is missing")
}
I intend to record the errors in my R code while calling functions in a dataframe (ERR_LOG, say). I want to use 'try' to identify errors while calling a function,if any.The dataframe(ERR_LOG) will have the following columns :
Time : The time at which the function was called (Sys.time)
Loc : For which function call was this error recorded (name of the
function)
Desc : Description of the error which R throws at us (Error message
in R)
Example :
First I would like to initialize a blank dataframe 'ERR_LOG' with these columns
Then write the function
f <- function(a){
x <- a*100
return(x)
}
Now I put the output of the call to 'f' in 'chk'
chk <- try(f())
The above call gives the error 'Error in a * 100 : 'a' is missing' (description of the error)
Check
if(inherits(chk,'try-error'))
{then I want to populate ERR_LOG and stop the code execution}
How can this be done in R?
use tryCatch instead of try
Then inside tryCatch(), use the argument error=function(e){}
e will have an element named message, which is what you would like
Use the following call with browser to explore e$message:
x <- tryCatch(stop("This is your error message"), error=function(e) {browser()})
Note that your function need not be anonymous.
MyErrorParser <- function(e) {
m <- e$message
if (grepl("something", m))
do something
return (something_else)
}
## THEN
tryCatch(stop("This is a test"), error=MyErrorParser)
S4 classes allow you to define validity checks using validObject() or setValidity(). However, this does not appear to work for ReferenceClasses.
I have tried adding assert_that() or if (badness) stop(message) clauses to the $initialize() method of a ReferenceClass. However, when I simulate loading the package (using devtools::load_all()), it must try to create some prototype class because the initialize method executes and fails (because no fields have been set).
What am I doing wrong?
Implement a validity method on the reference class
A = setRefClass("A", fields=list(x="numeric", y="numeric"))
setValidity("A", function(object) {
if (length(object$x) != length(object$y)) {
"x, y lengths differ"
} else NULL
})
and invoke the validity method explicitly
> validObject(A())
[1] TRUE
> validObject(A(x=1:5, y=5:1))
[1] TRUE
> validObject(A(x=1:5, y=5:4))
Error in validObject(A(x = 1:5, y = 5:4)) :
invalid class "A" object: x, y lengths differ
Unfortunately, setValidity() would need to be called explicitly as the penultimate line of an initialize method or constructor.
Ok so you can do this in initialize. It should have the form:
initialize = function (...) {
if (nargs()) return ()
# Capture arguments in list
args <- list(...)
# If the field name is passed to the initialize function
# then check whether it is valid and assign it. Otherwise
# assign a zero length value (character if field_name has
# that type)
if (!is.null(args$field_name)) {
assert_that(check_field_name(args$field_name))
field_name <<- field_name
} else {
field_name <<- character()
}
# Make sure you callSuper as this will then assign other
# fields included in ... that weren't already specially
# processed like `field_name`
callSuper(...)
}
This is based on the strategy set out in the lme4 package.
For a dataset of "Baltimore homicides"
It is required to create a function that takes a string for example "shooting" and return an integer represents the count of victims of "shooting".
I wrote the following function but i receive errors
Error: unexpected '}' in " }"
Error: object 'counti' not found
I also cant figure out if the ==Null is correct
count <- function(cause = NULL) {
## Check that "cause" is non-NULL; else throw error
if cause==NULL
{
stop()
print("no cause provided")
}
## Read "homicides.txt" data file
homicides <- readLines("homicides.txt")
## Extract causes of death
i <- grep(cause, homicides) ##get indices of cause
counti <- lenghth(i) ##get count of indices
## Check that specific "cause" is allowed; else throw error
if counti=0
{
stop()
print("no such cause")
}
## Return integer containing count of homicides for that cause
return(counti)
}
this is my working function after edit, thanks guys
count <- function(cause = NULL) {
if(missing(cause) | is.null(cause)) stop("no cause provided")
homicides <- readLines("homicides.txt")
i=length(grep(cause, homicides))
if(i==0) stop("no cause found")
return(i)
}
You can simplify your function to 2 lines by doing this:
count <- function(cause = NULL, data) {
if(is.null(cause)) stop("no cause provided")
length(grep(cause, data))
}
data <- c("murder", "some other cause")
count("murder", data)
[1] 1
Note the following principles:
R has many features of a functional language. This means that each function should, as far as possible, depend only on the arguments you pass it.
When you have a bug in your code, simplify it to the shortest possible version, fix the bug, then build out from there.
Also, keep stop() for really fatal errors. Not finding a search string in your data isn't an error, it simply means the cause wasn't found. You don't want your code to stop. At most, issue a message() or a warning().