[Rd] simplify2array assumes non-NA dim() -- base or method bug?

[Rui Barradas]

Hello,

I don't think it's a bug in ncol.
nrow and ncol are not generic, they are defined simply as

nrow <- function(x) dim(x)[1L]
ncol <- function(x) dim(x)[2L]

Checking:

nrow
#function (x)
#dim(x)[1L]
#<bytecode: 0x000001c3e2863c78>
#<environment: namespace:base>

ncol
#function (x)
#dim(x)[2L]
#<bytecode: 0x000001c3e1f8c030>
#<environment: namespace:base>


Since dim(table(letters)) returns a length 1 vector, nrow returns that 
value and ncol's return is the expected behavior of subsetting past the 
vector length.

dim(table(letters))  # length 1
# [1] 26

nrow(table(letters))  # works as expected
# [1] 26

ncol(table(letters))  # works as expected
# [1] NA


Hope this helps,

Rui Barradas




Às 04:19 de 26/08/2022, Michael Chirico via R-devel escreveu:
> Does this somewhat contradict the requirement that dimensions are non-missing?
> 
> ncol(table(letters))
> # [1] NA
> 
> On the other hand,
> 
> dim(table(letters))
> # [1] 26
> 
> Maybe that's a bug for the ncol() method of table?
> 
> On Thu, Aug 25, 2022 at 2:55 AM Sebastian Meyer <seb.meyer using fau.de> wrote:
>>
>> Hmm. I think I haven't seen NA dims in base R before. R-lang says
>>
>>> The 'dim' attribute is used to implement arrays.  The content of
>>> the array is stored in a vector in column-major order and the 'dim'
>>> attribute is a vector of integers specifying the respective extents of
>>> the array.  R ensures that the length of the vector is the product of
>>> the lengths of the dimensions.
>>
>> And R-intro says:
>>
>>> A dimension vector is a vector of non-negative integers.
>>
>> I understand "vector of [non-negative] integers" as excluding NA_integer_.
>>
>> Correspondingly:
>>
>>> a <- 1
>>> dim(a) <- NA_integer_
>>
>> Error in dim(a) <- NA_integer_ : the dims contain missing values
>>
>>> matrix(1, NA_integer_)
>>
>> Error in matrix(1, NA_integer_) : invalid 'nrow' value (too large or NA)
>>
>>> array(1, NA_integer_)
>>
>> Error in array(1, NA_integer_) : negative length vectors are not allowed
>>
>> There must be many more examples where non-NULL dim() is assumed to
>> not contain missing values.
>>
>> simplify2array() aligns with that specification and only needs to check
>> for numeric (non-NULL) dims at this point and not also !anyNA(c.dim).
>> So my take is that there is no bug.
>>
>> Best regards,
>>
>>          Sebastian Meyer
>>
>>
>> Am 25.08.22 um 04:51 schrieb Michael Chirico via R-devel:
>>> If any component of the dim() returned as c.dim here[1] are missing,
>>> simplify2array() errors inscrutably (specifically, because the last &&
>>> condition is missing):
>>>
>>> Error in if (higher && length(c.dim <- unique(lapply(x, dim))) == 1 &&  :
>>>     missing value where TRUE/FALSE needed
>>>
>>> At root here is that dim.tbl_lazy ({dbplyr} package method [2]) very
>>> intentionally neglects to count the # of rows in the result -- the
>>> whole point of a lazy table is to avoid calculating full queries
>>> unless specifically requested, so the # of rows is left as missing,
>>> i.e., there _is_ a quantity of rows, but the exact number is not
>>> known.
>>>
>>> That seems to me like a proper usage of NA, and hence this is a
>>> simplify2array() bug, but I am curious other thoughts here before
>>> attempting a patch.
>>>
>>> [1] https://github.com/r-devel/r-svn/blob/2d4f8c283d53ff2c98d92c7b77b11e652297742c/src/library/base/R/sapply.R#L46-L48
>>> [2] https://github.com/tidyverse/dbplyr/blob/36b146e36d6d9af215dc48e60862d4b807b9e606/R/tbl-lazy.R#L45-L47
>>>
>>> ______________________________________________
>>> R-devel using r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
> 
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