I'm writing a simple function that takes two arguments (state, outcome). State is used to subset a dataframe later.
Having said that, part of the requirement is that state be a length 2 character vector. I need to write more code to ensure that the state that is passed conforms to this requirement.
So I wrote the following:
best <- function(state, outcome) {
outcome <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
state <- vector(mode = "character", length = 2)
st.checkTbl <- outcome[8]
state
}
However, when I call the function and pass the arguments:
best("AXA") or best("FOO") or even best("TX") or best(AL)
All I get back is: "" ""
If I comment out the #state <- ... then it passes the argument just fine and it prints "FOO" or "AXA" or "TX", etc.
How can I ensure that the argument passed to the function is stored as a variable (state) in the function? Or, am I way overthinking this? Really I just wanted to test that what I am passing to the state argument can be printed for test purposes.
. Sorry for the 101 lesson.
You would generally read your data outside of any function, like so:
outcome.data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
Otherwise, since a function has its own namespace, all the variables defined inside of it will vanish upon its return, unless they themselves are returned by the function with return(...). Several objects can be returned by putting them in a list: return(list(item1=var1, item2=var2)).
Some functions, such as assign, have the envir parameter that can be set to .GlobalEnv to change this behavior. Altering an object can also be done inside a function using the <<- operator instead of <-, although this practice is generally recommended against.
As a side note, when using a function, you need to define clearly:
What are its inputs
What does it do
What does it return
It's not useful, for instance, to use outcome as a function parameter and then read into a variable named income the content of a csv file. Your argument is then useless as it will be written over. That's why you had to comment out the line defining your state variable inside the function to actually be able to use state as it was received by the function.
This surely won't answer all your questions, but hopefully it can help you clarify certain things. For the rest there are plenty of good tutorials to learn further on how to program in R and how/when to use functions. Best of luck and happy learning!
Related
Consider the following:
y<-c("A","B","C")
x<-z<-c(1,2,3)
names(x)<-y
"names<-"(z,y)
If you run this code, you will discover that names(x)<-y is not identical to "names<-"(z,y). In particular, one sees that names(x)<-y actually changes the names of x whereas "names<-"(z,y) returns z with its names changed.
Why is this? I was under the impression that the difference between writing a function normally and writing it as an infix operator was only one of syntax, rather than something that actually changes the output. Where in the documentation is this difference discussed?
Short answer: names(x)<-y is actually sugar for x<-"names<-"(x,y) and not just "names<-"(x,y). See the the R-lang manual, pages 18-19 (pages 23-24 of the PDF), which comes to basically the same example.
For example, names(x) <- c("a","b") is equivalent to:
`*tmp*`<-x
x <- "names<-"(`*tmp*`, value=c("a","b"))
rm(`*tmp*`)
If more familiar with getter/setter, one can think that if somefunction is a getter function, somefunction<- is the corresponding setter. In R, where each object is immutable, it's more correct to call the setter a replacement function, because the function actually creates a new object identical to the old one, but with an attribute added/modified/removed and replaces with this new object the old one.
In the case example for instance, the names attribute are not just added to x; rather a new object with the same values of x but with the names is created and linked to the x symbol.
Since there are still some doubts about why the issue is discussed in the language doc instead directly on ?names, here is a small recap of this property of the R language.
You can define a function with the name you wish (there are some restrictions of course) and the name does not impact in any way if the function is called "normally".
However, if you name a function with the <- suffix, it becomes a replacement function and allows the parser to apply the function with the mechanism described at the beginning of this answer if called by the syntax foo(x)<-value. See here that you don't call explicitely foo<-, but with a slightly different syntax you obtain an object replacement (since the name).
Although there are not formal restrictions, it's common to define getter/setter in R with the same name (for instance names and names<-). In this case, the <- suffix function is the replacement function of the corresponding version without suffix.
As stated at the beginning, this behaviour is general and a property of the language, so it doesn't need to be discussed in any replacement function doc.
In particular, one sees that names(x)<-y actually changes the names of x whereas "names<-"(z,y) returns z with its names changed.
That’s because `names<-`1 is a regular function, albeit with an odd name2. It performs no assignment, it returns a new object with the names attribute set. In fact `names<-` is a primitive function in R but it could be implemented as follows (there are shorter, better ways of writing this in R, but I want the separate steps to be explicit):
`names<-` = function (x, value) {
new = x
attr(new, 'names') = value
new
}
That is, it
… creates a new object that’s a copy of x,
… sets the names attribute on that newly created object, and
… returns the new object.
Since virtually all objects in R are immutable, this fits naturally into R’s semantics. In fact, a better name for this exact function would be with_names3. But the creators of R found it convenient to be able to write such an assignment without repeating the name of the object. So instead of writing
x = with_names(x, c('foo', 'bar'))
or
x = `names<-`(x, c('foo', 'bar'))
R allows us to write
names(x) = c('foo', 'bar')
R handles this syntax specially by internally converting it to another expression, documented in the Subset assignment section of the R language definition, as explained in the answer by Nicola.
But the gist is that names(x) = y and `names<-`(x, y) are different because … they just are. The former is a special syntactic form that gets recognised and transformed by the R parser. The latter is a regular function call, and the weird function name is a red herring: it doesn’t affect the execution whatsoever. It does the same as if the function was named differently, and you can confirm this by assigning it a different name:
with_names = `names<-`
`another weird(!) name` = `names<-`
# These are all identical:
`names<-`(x, y)
with_names(x, y)
`another weird(!) name`(x, y)
1 I strongly encourage using backtick quotes (`) instead of straight quotes (' or ") to quote R variable names. While both are allowed in some circumstances, the latter invites confusion with strings, and is conceptually bonkers. These are not strings. Consider:
"a" = "b"
"c" = "a"
Rather than copy the value of a into c, what this code actually does is set c to literal "a", because quotes now mean different things on the left- and right-hand side of assignment.
The R documentation confirms that
The preferred quote [for variable names] is the backtick (`)
2 Regular variable names (aka “identifiers” or just “names”) in R can only contain letters, digits, underscore and the dot, must start with a letter, or with a dot not followed by a digit, and can’t be reserved words. But R allows using pretty much arbitrary characters — including punctuation and even spaces! — in variable names, provided the name is backtick-quoted.
3 In fact, R has an almost-alias for this function, called setNames — which isn’t a great name, since set… implies mutating the object, but of course it doesn’t do that.
I want to, essentially, pass a value untouched through a function. So in the following example (in Rstudio):
example_function <- function(datain){
as.environment("package:utils")$View(datain)
}
I want the inner function to act as if I'm passing it the original object, in particular so the name which appears in the View window will have the name of the original object (X, say) rather than datain which is what currently occurs.
With deparse(substitute(datain)) you can get the original name of the argument passed.
Then, to accomplish what you asked for, you can simply do
example_function <- function(datain){
as.environment("package:utils")$View(datain, deparse(substitute(datain)))
}
Now the View window will be titled appropriately as you wanted.
However note that "I want the inner function to act as if I'm passing it the original object" request of yours is not possible in R. R does not support pass-by-reference. There are some workarounds, but if you only needed if for naming the View, the above fix should be fine.
You can also use get for this.
example_function <- function(datain){
as.environment("package:utils")$View(get(datain),datain)
}
in this case you don't pass the variable but rather the name of the variable as a string.
example_function("X")
Suppose I have in my shiny ui.R an input:
selectInput("choice","Select Values",choices=c('a','b','c',FALSE),
selected="FALSE")
And I want to use this input as a parameter to a function in server.R. The default value for this parameter is FALSE, but can take in character values. I want to set it so that, for example, if the user select 'a', the value 'a' would be passed on to the parameter in the function, and if the user select 'FALSE', the default value of FALSE is passed on to the parameter.
The way I tried to do this is by:
choice <- ifelse(input$choice=='FALSE',FALSE,input$choice)
and then use it in the function:
sample_func(param=choice)
However, this gives me an error "param has the wrong format". The error is the result of choice not being a character value or FALSE.
What might be the reason for this?
The first problem is:
choice <- ifelse(input$choice=='FALSE',FALSE,input$choice)
This must be written in a reactive context as it depends on user input. So you have to wrap your ifelse(...) part in reactive(). Of course I don't know if you had done so already since you didn't post the entire code and I assume you just wrote that code without the wrapping of reactive().
Another thing concerning this same line is not really a bug, but a habit. It's a bad idea to use choice again. The point is, it already existed as in input$choice and now you assign it to a reactive value of the same name. That could be confusing if you have a complex and long code.
So, I would suggest something like this below.
fun_choice <- reactive(ifelse(input$choice=='FALSE',FALSE,input$choice))
The next problem is in:
sample_func(param=fun_choice) ## I changed the argument name to fun_choice
If you had treated fun_choice as reactive, That should be replaced by fun_choice(). Also, that would mean that this function result should also be in reactive context. So the line should become:
variable_name <- reactive( sample_func(param=fun_choice()) )
Of course, it could be wrapped in observe if what you want is the side effect and some other things but not the function return.
Hope this help.
One last thing, if fun_choice is of no other use elsewhere but just passing into sample_func, I would suggest you put them in one reactive(). i.e.
variable_name <- reactive({
fun_choice <- ifelse(input$choice == 'FALSE', FALSE, input$choice)
sample_func(param = fun_choice)
})
Note that in this method, fun_choice, within the same reactive(), need not be expressed as fun_choice(), but simply fun_choice.
Am R newb. I coded a function that uses 3 parameters. In my code i use one of the parameters to help me read files from a directory. There are 100 files in the directory. The code works fine when I pass it all the function parameters and specify the files i want to read.
functionX(var1, var2, id) and functionX(var1, var2, id = 1:100)
## Below is the first line of code for me that uses "id".
sub.file.names <- file.names[id] ### Get file names
The odd thing is that when a value for "id" is not passed to the function initially (or set with a 1:100 default), the code seems to read all the file names anyway. And it does so even though a value for "id" has never been established.
It's as if R somehow treats the two functions below the same when the user omits passing a value to "id" when executing the function ... eg, functionx("var1", "var2") ## and does not pass any id variable
functionx(var1, var2, id)
functionx(var1, var2, id = 1:100)
Any pointers on why this is happening would be great to know. I feel the answer is obvious, but have not been able to figure it out.
Let me try to explain what is happening with a simple example. Consider the following function
foo = function(i){
LETTERS[i]
}
When you try foo(), you will notice that the function returns all 26 uppercase letters. Why does that happen? Well, everything in R is a function. So when you say LETTERS[i], you are essentially calling the function [. So, the function call is
`[`(LETTERS, i)
Since i is missing, this call is executed as [(LETTERS) (essentially LETTERS[]) which returns all elements of the vector. Note that this occurs because the [ function allows for the i argument to be missing while calling it. Check ?[
If you want the function to act differently when id is missing, either check for missing(id), or explicitly set it to NULL as default. So, if you do
foo2 = function(i = NULL){
LETTERS[i]
}
foo2() will return a zero length character vector.
Say that I have the following function:
myfun <- function(x){
assignee <- get_assignee_name()
message(paste0("output assigned to ",assignee,"!"))
x
}
my_var <- myfun(7)
output assigned to my_var!
I am looking for something that does the job of get_assignee_name() above.
It should be a function or a few lines of code that is called from inside a function, it examines the call that it occurs inside of and returns the object that is being assigned to as a character, if one exists. So in the example
answer <- myfun(10)
the message "output assigned to answer!" should appear.
I am aware that this seems unnecessarily complicated, but it is just an example to demonstrate the point for a more complicated use case. I am also aware that of ways around this involving passing the variable name into the function as a parameter and then calling assign. This won't solve the problem in this case, where this should be transparent to the user
This is not possible because <- is a primitive and quite special function. It is not part of the call stack. You would need to use assign instead:
myfun <- function(x){
assignee <- sys.call(1)
if (assignee[[1]] == quote(assign))
message(paste0("output assigned to ",assignee[[2]],"!"))
x
}
assign("my_var", myfun(7))
#output assigned to my_var!
my_var
#[1] 7
However, I suggest you reconsider how you approach your actual issue.