Bug: train_continuous() with integer64

[teunbrand]

Currently, train_continuous() gives nonsensical ranges for integer64 input.

library(scales)

new <- bit64::as.integer64(1:10)

train_continuous(new)
#> [1] 4.940656e-324 4.940656e-323

Looking at the the base::range.default function, it seems that concatenating NULL with an integer64 vector causes weird casting behaviour. This doesn't happen using the vctrs::vec_c() function for example.

existing <- NULL

c(existing, new)
#>  [1] 4.940656e-324 9.881313e-324 1.482197e-323 1.976263e-323 2.470328e-323
#>  [6] 2.964394e-323 3.458460e-323 3.952525e-323 4.446591e-323 4.940656e-323

vctrs::vec_c(existing, new)
#> integer64
#>  [1] 1  2  3  4  5  6  7  8  9  10

^{Created on 2022-11-05 by the reprex package (v2.0.1)}

There are a few options to prevent this. In the following line

scales/R/scale-continuous.r

Line 49 in f7056ad

suppressWarnings(range(existing, new, na.rm = TRUE, finite = TRUE))

The input can be pre-combined:

suppressWarnings(range(vctrs::vec_c(existing, new), na.rm = TRUE, finite = TRUE))

The input can be coerced to numeric:

suppressWarnings(range(existing, as.numeric(new), na.rm = TRUE, finite = TRUE))

Or can be branched depending on the 'null'-ness of existing.

if (is.null(existing)) {
  suppressWarnings(range(new, na.rm = TRUE, finite = TRUE))
} else {
  suppressWarnings(range(existing, new, na.rm = TRUE, finite = TRUE))
}