EDIT: Hadley Wickham points out that I misspoke. R CMD check is throwing NOTES, not Warnings. I'm terribly sorry for the confusion. It was my oversight.
The short version
R CMD check throws this note every time I use sensible plot-creation syntax in ggplot2:
no visible binding for global variable [variable name]
I understand why R CMD check does that, but it seems to be criminalizing an entire vein of otherwise sensible syntax. I'm not sure what steps to take to get my package to pass R CMD check and get admitted to CRAN.
The background
Sascha Epskamp previously posted on essentially the same issue. The difference, I think, is that subset()'s manpage says it's designed for interactive use.
In my case, the issue is not over subset() but over a core feature of ggplot2: the data = argument.
An example of code I write that generates these notes
Here's a sub-function in my package that adds points to a plot:
JitteredResponsesByContrast <- function (data) {
return(
geom_point(
aes(
x = x.values,
y = y.values
),
data = data,
position = position_jitter(height = 0, width = GetDegreeOfJitter(jj))
)
)
}
R CMD check, on parsing this code, will say
granovagg.contr : JitteredResponsesByContrast: no visible binding for
global variable 'x.values'
granovagg.contr : JitteredResponsesByContrast: no visible binding for
global variable 'y.values'
Why R CMD check is right
The check is technically correct. x.values and y.values
- Aren't defined locally in the function
JitteredResponsesByContrast() - Aren't pre-defined in the form
x.values <- [something]either globally or in the caller.
Instead, they're variables within a dataframe that gets defined earlier and passed into the function JitteredResponsesByContrast().
Why ggplot2 makes it difficult to appease R CMD check
ggplot2 seems to encourage the use of a data argument. The data argument, presumably, is why this code will execute
library(ggplot2)
p <- ggplot(aes(x = hwy, y = cty), data = mpg)
p + geom_point()
but this code will produce an object-not-found error:
library(ggplot2)
hwy # a variable in the mpg dataset
Two work-arounds, and why I'm happy with neither
The NULLing out strategy
Matthew Dowle recommends setting the problematic variables to NULL first, which in my case would look like this:
JitteredResponsesByContrast <- function (data) {
x.values <- y.values <- NULL # Setting the variables to NULL first
return(
geom_point(
aes(
x = x.values,
y = y.values
),
data = data,
position = position_jitter(height = 0, width = GetDegreeOfJitter(jj))
)
)
}
I appreciate this solution, but I dislike it for three reasons.
- it serves no additional purpose beyond appeasing
R CMD check. - it doesn't reflect intent. It raises the expectation that the
aes()call will see our now-NULL variables (it won't), while obscuring the real purpose (making R CMD check aware of variables it apparently wouldn't otherwise know were bound) - The problems of 1 and 2 multiply because every time you write a function that returns a plot element, you have to add a confusing NULLing statement
The with() strategy
You can use with() to explicitly signal that the variables in question can be found inside some larger environment. In my case, using with() looks like this:
JitteredResponsesByContrast <- function (data) {
with(data, {
geom_point(
aes(
x = x.values,
y = y.values
),
data = data,
position = position_jitter(height = 0, width = GetDegreeOfJitter(jj))
)
}
)
}
This solution works. But, I don't like this solution because it doesn't even work the way I would expect it to. If with() were really solving the problem of pointing the interpreter to where the variables are, then I shouldn't even need the data = argument. But, with() doesn't work that way:
library(ggplot2)
p <- ggplot()
p <- p + with(mpg, geom_point(aes(x = hwy, y = cty)))
p # will generate an error saying `hwy` is not found
So, again, I think this solution has similar flaws to the NULLing strategy:
- I still have to go through every plot element function and wrap the logic in a
with()call - The
with()call is misleading. I still need to supply adata =argument; allwith()is doing is appeasingR CMD check.
Conclusion
The way I see it, there are three options I could take:
- Lobby CRAN to ignore the notes by arguing that they're "spurious" (pursuant to CRAN policy), and do that every time I submit a package
- Fix my code with one of two undesirable strategies (NULLing or
with()blocks) - Hum really loudly and hope the problem goes away
None of the three make me happy, and I'm wondering what people suggest I (and other package developers wanting to tap into ggplot2) should do.
