Adaptive, left-aligned rolling max #5438
Description
I guess frollmax would be ideal here.
I would like to perform a rolling max using an (adaptive) non-equi join in data.table. Basing myself on this answer, I think I'm getting close, but not quite there.
For all rows of ex I need the max(value[row:end_window])
> ex
time value end_window row
1: 2022-03-14 08:20:02 13344.77 540 1
2: 2022-03-14 08:20:02 13343.52 541 2
3: 2022-03-14 08:20:03 13342.27 547 3
4: 2022-03-14 08:20:04 13343.27 541 4
5: 2022-03-14 08:20:04 13343.02 541 5
I tried calculating rollmax like so:
res <-ex[ex,.(value,row,end_window),on=.(row>=row,row<=end_window)][
,.(rollmax = max(value), end_window),by=.(row)]
but it isn't exactly what I expect. For row 1 it is correct because max(ex$value[1:540]) is indeed 13361.77.
res
row rollmax end_window
1: 1 13361.77 540
2: 1 13361.77 541
3: 1 13361.77 547
4: 1 13361.77 541
However, for row 596 this is not the case:
> res <- res[order(row)]
> res[596]
row end_window rollmax end_window row
1: 596 622 13327.42 622 596
> max(ex$value[596:622])
[1] 13328.67
Any idea?
Data:
> dput(ex)
structure(list(time = structure(c(1647246002.24923, 1647246002.79761,
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