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Today I was putting some code together that made plots from slices of a 3-dimensional `array` object `aa`. A couple of the dimensions in `aa` had names defined by named vectors. For example:

```> aa = array(runif(2*3*4),
dim=c(2,3,4),
dimnames=list(id  = c(good='id1', evil='id2'),
x   = c(1,2,3),
var = c(up='a', dn='b', lt='c', rt='d')))
> str(aa)
num [1:2, 1:3, 1:4] 0.0138 0.2942 0.7988 0.3465 0.8751 ...
- attr(*, "dimnames")=List of 3
..\$ id : Named chr [1:2] "id1" "id2"
.. ..- attr(*, "names")= chr [1:2] "good" "evil"
..\$ x  : chr [1:3] "1" "2" "3"
..\$ var: Named chr [1:4] "a" "b" "c" "d"
.. ..- attr(*, "names")= chr [1:4] "up" "dn" "lt" "rt"```

Thus, I could access “aliases” for dimension names in `id` and `var` by:

```> names(dimnames(aa)\$id)
 "good" "evil"
> names(dimnames(aa)\$var)
 "up" "dn" "lt" "rt"```

The code I wrote would iterate over the 3rd dimension, using the resulting 2D `array`’s to produce a series of plots using `matplot()`. To make legends more readable, I made use of the `names` attribute for `dimnames` as above. In the first version, I used `apply()` to do the iterating:

```> apply(aa, 3, function(xy) {
x = as.numeric(dimnames(xy)\$x)
matplot(x, y=t(xy))
legend('topleft', legend=names(dimnames(xy)\$id), fill=1:nrow(xy))

NULL
})```

This worked perfectly fine, however, later I decided it would be more informative to use the names in the iterating dimension for a plot title. So I refactored a bit to use `sapply()`:

```> sapply(1:dim(aa), function(k) {
xy = aa[,,k]

x = as.numeric(dimnames(xy)\$x)
matplot(x, y=t(xy))
legend('topleft', legend=names(dimnames(xy)\$id), fill=1:nrow(xy))

title(main=names(dimnames(aa)\$var[k]))

NULL
})```

I was a little surprised that this threw an error indicating that the names associated with `dimnames(aa)\$id` were non-existant:

``` Error in legend("topleft", legend = names(dimnames(xy)\$id), fill = 1:nrow(xy)) :
'legend' is of length 0 ```

Upon inspection, it seems that it is R’s default behavior to drop attributes on `dimnames` when an `array` is subsetted.

```> str(aa[,,1])
num [1:2, 1:3] 0.0138 0.2942 0.7988 0.3465 0.8751 ...
- attr(*, "dimnames")=List of 2
..\$ id: chr [1:2] "id1" "id2"
..\$ x : chr [1:3] "1" "2" "3"```

Adding a `drop=FALSE` to the indexing doesn’t work. The only fix I could come up with was to reassign the additional attributes after subsetting:

```> sapply(1:dim(aa), function(k) {
xy = aa[,,k]

# !! recover additional dimname attributes
#    dropped by subsetting !! #
dimnames(xy) = dimnames(aa)[names(dimnames(aa)) %in% names(dimnames(xy))]

x = as.numeric(dimnames(xy)\$x)
matplot(x, y=t(xy))
legend('topleft', legend=names(dimnames(xy)\$id), fill=1:nrow(xy))

title(main=names(dimnames(aa)\$var[k]))

NULL
})```

To the greater R community, I ask – is this behavior a flaw, or was it done on purpose? If the latter, I pleadingly ask WHYYYYyyyyyyyy!

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