When I'm using a new function, the documentation/vignettes give an overview of how the function works, but often do not list all of the possible options for every argument.
There must (?) be a command which lists all of the valid options for an argument? After lots of Googling there are lots of answers to the question of how to list all the possible arguments of a function (args, formals etc), but nothing I can find which lists all the possible options of an argument?
For example if I type formals(lmer) or args(lmer), it just list the functions and the defaults, not all the possible options.
How can I display all the possible options that an argument can take?
Related
Help files call attributes() a function. Its syntax looks like a function call. Even class(attributes) calls it a function.
But I see I can assign something to attributes(myobject), which seems unusual. For example, I cannot assign anything to log(myobject).
So what is the proper name for "functions" like attributes()? Are there any other examples of it? How do you tell them apart from regular functions? (Other than trying supposedfunction(x)<-0, that is.)
Finally, I guess attributes() implementation overrides the assignment operator, in order to become a destination for assignments. Am I right? Is there any usable guide on how to do it?
Very good observation Indeed. It's an example of replacement function, if you see closely and type apropos('attributes') in your R console, It will return
"attributes"
"attributes<-"
along with other outputs.
So, basically the place where you are able to assign on the left sign of assignment operator, you are not calling attributes, you are actually calling attributes<- , There are many functions in R like that for example: names(), colnames(), length() etc. In your example log doesn't have any replacement counterpart hence it doesn't work the way you anticipated.
Definiton(from advanced R book link given below):
Replacement functions act like they modify their arguments in place,
and have the special name xxx<-. They typically have two arguments (x
and value), although they can have more, and they must return the
modified object
If you want to see the list of these functions you can do :
apropos('<-$') and you can check out similar functions, which has similar kind of properties.
You can read about it here and here
I am hopeful that this solves your problem.
I notice in different packages it sometimes refers to a variable, a column to sort by, an object, etc. Like in dplyr it usually refers to a variable, but in ggplot, it's not even used.
Is there any logic behind this? Is there any universality? Or can it just be anything.
It can accept an arbitrary number of formal parameters. In base R these parameters are often arguments to other functions. The Arguments description in the function's help page should indicate which subsequent functions will be getting these arguments. It can be the only argument, the first, the last, or it can be intercalated in the parameter list. The items in the list(...) generally should be named. You can access the items in the "dots" list in a couple of different ways: ...() and list(...) are two that I've seen. Generally, it is the R-cognoscenti that will be designing functions with these forms. When it is intercalated (or the first), the named parameters that follow it in the formals must be named when the function is called and cannot be assigned positionally. If you type ?'...' you will be shown the Reserved page, which in turn has a link to dotsMethods {methods}.
I found it difficult to search for [r] with "..." using a SO search panel but searching on "[r] dotsMethods" brought up 10 hits.
Im using R for about 3 years and one of the main advantages (in my opinion) is the wide range of questions and assistance one can find on stackoverflow and similar websites.
One thing that is missing and kind of annoys me is an entire list of every single argument a function can use (plus possible values of those arguments).
For example: In R documentation all "main" arguments are listed and in many cases the documentation says "... further arguments passed to or from other methods". How can I know which arguments are meant by "..."?
When searching on stackoverflow for a way to get my desired result of an analysis I sometimes stumble about these additional arguments which can be very helpful in many cases. It still takes much time to find these arguments hidden in other users answers. Sometimes I used a workaround which would have been unnecessary if I had known some additional function arguments.
Is anyone else experiencing the same thing?
(It's difficult to mention examples but I remember having that trouble when using the leaflet functions for the first time.)
Tim
The most direct answer is that we often don't know what arguments one might want to pass to .... In fact, that is the point of ... arguments, is to not require us to know what arguments may be passed to it.
Consider, for example, the print generic in base R. It is defined as
print(x, ...)
So what are the arguments that can be passed to ...?
print.factor defines
print(x, quote = FALSE, max.levels = NULL,
width = getOption("width"), ...)
print.table defines
print(x, digits = getOption("digits"), quote = FALSE,
na.print = "", zero.print = "0", justify = "none", ...)
Notice that the print methods for factor and table objects don't share the same arguments. In fact, every print method may be defined with a different set of arguments. R then uses the class of the object to determine which set of arguments to apply to print.
When a developer creates a new print method, CRAN requires that all new methods contain at least the same arguments as the generic. So every print method has arguments x and ....
How do I know what arguments may be acceptable to ...?
First, read and follow the documentation. In glm, you find that the ... argument accepts arguments to "form the default control argument." This references the control argument, which then references the glm.control function. Opening ?glm.control shows the arguments epsilon, maxit and trace.
Another example, in ggplot2's geom_line, the documentation states that ... arguments are passed to the layer function. Use ?layer to see what arguments are available.
If the documentation simply specifies "to other methods," then you are probably looking at a method that is dispatched with different behaviors for different types of objects.
This question already has answers here:
How to use R's ellipsis feature when writing your own function?
(5 answers)
Closed 8 years ago.
I'm trying to understand ... and/or (...) in R. I understand that somehow this is used for entering unknown or multiple parameters to a function, but when is this necessary and/or useful? I've searched rdocumentation for it, but found nothing. In the R Language Definition it is defined but in very abstract terms.
Hence I ask: why is ... useful? Is it just not sloppy coding? Wouldn't it be better to pass arguments explicitly?
It's called varargs (short for variadic arguments).
when is this necessary?
It's not strictly necessary, and it's not inherently sloppy. The "non-sloppy" alternative to varargs in any language is to pass an array or list as a single variable. So varargs is just syntactic sugar on top of a collection of things.
[when is it] useful?
Any time you want to save a few keystrokes and implicitly construct a list when calling a function.
Wouldn't it be better to pass arguments explicitly?
Depends. What are your criteria?
The ellipsis gives you the possibility to define functions with an unknown number of arguments/parameters.
It necessary for functions like c or list where the number of arguments given by the user is unknown.
If you type c or list in the R console you'll see that both of these functions use ... as arguments.
In these two cases it would be hard to pass arguments explicitly since the user can pass as many arguments as needed.
You can look at this post for more examples
Usually in html help of a package in R argument list, ends with
........ other arguments passed.
but how can we print all the arguments of a function in R.
If I understand your question correctly, then I tend to say: Most of the time, it is not possible to list all the possible arguments that may be passed under the ... 'section' of the function.
Please look at the very simple ?plot function. There, only two arguments, x and y are given on the help page. However, under ... there is a range of additional possible arguments. Most of them are (as the help page says) graphical parameters. In the ?lm case, I understand that the arguments in ... are passed to lm.fit and lm.wfit. Check those help pages to see which parameters these functions take.
I guess the main problem is that you have to check ALL functions, that arguments under ... may be passed to, to know ALL the possible arguments that may be passed under .... Since the number of functions may be very large, also the number of arguments working in ... may be very large. So we don't want to have them on the "top-level" help page.
I hope that made any sense...