Open MichaelChirico opened 11 months ago
Closes #1350
Alternatively, we can use a set.seed(), but keeping this test random does make it slightly more interesting.
set.seed()
I also tried with n=150, it fails ~0.05% of the time. I didn't notice a speed difference on n=150/n=200, so I stuck with the safer n=200.
n=150
n=200
Another option is to deterministically ensure 1:15 are present, e.g. instead of sample.int(15, 100, TRUE), we do c(1:15, sample.int(15, 85, TRUE)).
1:15
sample.int(15, 100, TRUE)
c(1:15, sample.int(15, 85, TRUE))
Closes #1350
Alternatively, we can use a
set.seed()
, but keeping this test random does make it slightly more interesting.I also tried with
n=150
, it fails ~0.05% of the time. I didn't notice a speed difference onn=150
/n=200
, so I stuck with the safern=200
.