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Improved verbose messages in rolling functions frolladaptivefun and frollfun #7733

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be1b189
Merge pull request #1 from Rdatatable/master
aidengseay Apr 29, 2026
5d80b2b
Adding updated files
kkarissa Apr 30, 2026
5239716
Updated NEWS.md
kkarissa Apr 30, 2026
f033f91
Updated test file
kkarissa Apr 30, 2026
09420a9
Fix test warnings and update output messages
kkarissa May 2, 2026
b8ae8e2
Resolve merge conflict in NEWS.md
kkarissa May 2, 2026
68a00f9
Update NEWS.md with new features and fixes
kkarissa May 2, 2026
47e4131
Change to ternary if operator
Omartech312 May 2, 2026
1c84904
Change to ternary if operator in froll.c
Omartech312 May 2, 2026
52fb2e8
Removing white space in froll.Rraw
Omartech312 May 3, 2026
1a167e4
Removing whitespace from NEWS.md
Omartech312 May 3, 2026
6d1a9a6
Refactoring rfunNames for copile time definition (in data.table.h)
Omartech312 May 4, 2026
dc621d7
Removing extra brackets
Omartech312 May 4, 2026
077e638
Declare extern array for roll function names
Omartech312 May 4, 2026
c41127a
Reverting changes for rfunStr & adjusting for direct use of rfunNames…
Omartech312 May 4, 2026
a51eb5d
Update comments for clarity in frolladaptive.c
Omartech312 May 4, 2026
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Removing spaces
Omartech312 May 6, 2026
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Remove unnecessary newline in frolladaptive.c
Omartech312 May 6, 2026
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Changing NEWS.md message
Omartech312 May 6, 2026
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Merge branch 'master' into master
ben-schwen May 6, 2026
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ben-schwen May 6, 2026
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4 changes: 4 additions & 0 deletions NEWS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,11 @@

5. `tables()` can now optionally report `data.table` objects stored one level deep inside list objects when `depth=1L`, [#2606](https://github.com/Rdatatable/data.table/issues/2606). Thanks @MichaelChirico for the report and @manmita for the PR

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6. `frolladaptivefun()` and `frollfun()` adjusted print statements for verbose messages to be more user friendly, [#7021](https://github.com/Rdatatable/data.table/issues/7021) Thanks @jangorecki for initiating the issue.
=======
6. `yearqtr()` and `yearmon()` now gain an optional format specifier [#7694](https://github.com/Rdatatable/data.table/issues/7694). 'numeric' is the default, which preserves the original behavior, but 'character' formats `yearqtr()` as YYYYQ# (e.g. 2025Q2) and `yearmon()` as YYYYM## (e.g. 2025M02, 2025M10). Thanks to @jan-swissre for the report and @LunaticSage218 for the implementation.
>>>>>>> be1b189a3d2ae59238c6bde09bf63296d8d849d9

### BUG FIXES

Expand Down
116 changes: 58 additions & 58 deletions inst/tests/froll.Rraw
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Expand Up @@ -308,36 +308,36 @@ test(6000.0671, frollmean(c(1:2,NA,4:10), 4), c(rep(NA_real_, 6), 5.5, 6.5, 7.5,
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
"frollmeanFast: non-finite values are present in input, skip non-finite unaware attempt and run with extra care for NFs straighaway",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"
))
))
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test(6000.0672, frollmean(c(1:2,NA,4:10), 4, has.nf=FALSE), c(rep(NA_real_, 6), 5.5, 6.5, 7.5, 8.5), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially.*single rolling computation.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 4, hasnf -1, narm 0",
"frollmeanFast: non-finite values are present in input, skip non-finite unaware attempt and run with extra care for NFs straighaway",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"
), warning="has.nf=FALSE used but non-finite values are present in input, use default has.nf=NA to avoid this warning")
), warning="has.nf=FALSE used but non-finite values are present in input, use default has.nf=NA to avoid this warning")
test(6000.0673, frollmean(c(1:2,NA,4:10), 2, has.nf=FALSE), c(NA, 1.5, NA, NA, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially.*single rolling computation.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 2, hasnf -1, narm 0",
"frollmeanFast: non-finite values are present in input, re-running with extra care for NFs",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"
), warning="has.nf=FALSE used but non-finite values are present in input, use default has.nf=NA to avoid this warning")
), warning="has.nf=FALSE used but non-finite values are present in input, use default has.nf=NA to avoid this warning")
test(6000.0674, frollmean(c(1:2,NA,4:10), 4, align="center"), c(rep(NA_real_, 4), 5.5, 6.5, 7.5, 8.5, NA, NA), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially.*single rolling computation.*",
"frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
"frollmeanFast: non-finite values are present in input, skip non-finite unaware attempt and run with extra care for NFs straighaway",
"frollfun: align 0, shift answer by -2",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"
))
))
options(datatable.verbose=FALSE)

#### fill constant
Expand Down Expand Up @@ -436,17 +436,17 @@ test(6000.1196, frollmean(c(1:5,NA), 1:6, algo="exact", na.rm=TRUE, adaptive=TRU
"frollfunR: 1:",
"frolladaptivemeanExact: running in parallel for input length 6, hasnf 0, narm 1",
"frolladaptivemeanExact: non-finite values are present in input, re-running with extra care for NFs",
"frolladaptivefun: processing fun 0 algo 1 took.*",
"frolladaptivefun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"
))
))
#### exact na.rm=TRUE verbose=TRUE
test(6000.1197, frollmean(c(1:5,NA), 2, algo="exact", na.rm=TRUE), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frollmeanExact: running in parallel for input length 6, window 2, hasnf 0, narm 1",
"frollmeanExact: non-finite values are present in input, re-running with extra care for NFs",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"
))
options(datatable.verbose=FALSE)
Expand Down Expand Up @@ -675,82 +675,82 @@ test(6000.171, frollmean(x, n), output=c(
"frollfunR: .*sequentially.*single rolling computation.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.172, frollmean(list(x, x+1), n), output=c(
"frollfunR: allocating memory for results 2x1",
"frollfunR: .*in parallel.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: 2:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.173, frollmean(x, c(n, n+1)), output=c(
"frollfunR: allocating memory for results 1x2",
"frollfunR: .*in parallel.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: 2:",
"frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.174, frollmean(list(x, x+1), c(n, n+1)), output=c(
"frollfunR: allocating memory for results 2x2",
"frollfunR: .*in parallel.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: 2:",
"frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: 3:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: 4:",
"frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.175, frollmean(x, n, algo="exact"), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"))
test(6000.176, frollmean(x, n, align="center"), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially.*single rolling computation.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: align 0, shift answer by -1",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.177, frollmean(x, n, align="left"), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially.*single rolling computation.*",
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollfun: align -1, shift answer by -2",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
nn = c(1:4,2:3,1:4)
test(6000.178, frollmean(x, nn, adaptive=TRUE), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially because adaptive.*",
"frollfunR: 1:",
"frolladaptivemeanFast: running for input length 10, hasnf 0, narm 0",
"frolladaptivefun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frolladaptivefun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.179, frollmean(x, nn, algo="exact", adaptive=TRUE), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frolladaptivemeanExact: running in parallel for input length 10, hasnf 0, narm 0",
"frolladaptivefun: processing fun 0 algo 1 took.*",
"frollfunR: processing.*took.*"))
"frolladaptivefun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"))

x[8] = NA
test(6000.180, frollmean(x, n), output=c(
Expand All @@ -759,59 +759,59 @@ test(6000.180, frollmean(x, n), output=c(
"frollfunR: 1:",
"frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
"frollmeanFast: non-finite values are present in input, re-running with extra care for NFs",
"frollfun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.181, frollmean(x, n, algo="exact"), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
"frollmeanExact: non-finite values are present in input, na.rm=FALSE and algo='exact' propagates NFs properply, no need to re-run",
"frollfun: processing fun 0 algo 1 took.*",
"frollfunR: processing.*took.*"))
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"))
test(6000.182, frollmean(x, nn, adaptive=TRUE), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*sequentially because adaptive.*",
"frollfunR: 1:",
"frolladaptivemeanFast: running for input length 10, hasnf 0, narm 0",
"frolladaptivemeanFast: non-finite values are present in input, re-running with extra care for NFs",
"frolladaptivefun: processing fun 0 algo 0 took.*",
"frollfunR: processing.*took.*"))
"frolladaptivefun: processing fun MEAN algo fast took.*",
"frollfunR: processing.*took.*"))
test(6000.183, frollmean(x, nn, algo="exact", adaptive=TRUE), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frolladaptivemeanExact: running in parallel for input length 10, hasnf 0, narm 0",
"frolladaptivemeanExact: non-finite values are present in input, na.rm=FALSE and algo='exact' propagates NFs properply, no need to re-run",
"frolladaptivefun: processing fun 0 algo 1 took.*",
"frollfunR: processing.*took.*"))
"frolladaptivefun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"))

d = as.data.table(list(1:10/2, 10:1/4))
test(6000.184, frollmean(d[,1], 3, algo="exact"), output=c(
"frollfunR: allocating memory for results 1x1",
"frollfunR: .*algo='exact' is already parallelised.*",
"frollfunR: 1:",
"frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"
))
))
test(6000.185, frollmean(d, 3:4, algo="exact"), output=c(
"frollfunR: allocating memory for results 2x2",
"frollfunR: .*sequentially.*algo='exact'.*already parallelised.*",
"frollfunR: 1:",
"frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: 2:",
"frollmeanExact: running in parallel for input length 10, window 4, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: 3:",
"frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: 4:",
"frollmeanExact: running in parallel for input length 10, window 4, hasnf 0, narm 0",
"frollfun: processing fun 0 algo 1 took.*",
"frollfun: processing fun MEAN algo exact took.*",
"frollfunR: processing.*took.*"
))
))
options(datatable.verbose=FALSE)

## test warnings
Expand Down Expand Up @@ -861,9 +861,9 @@ options(datatable.verbose=FALSE)

## frollmax adaptive
options(datatable.verbose=TRUE) ## adaptive frollmax no fast algo
test(6000.3, frollmax(1:4, c(2,2,2,2), adaptive=TRUE), output="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.3001, frollmax(1:4, c(2,2,2,2), algo="fast", adaptive=TRUE), output="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.3002, frollmax(1:4, c(2,2,2,2), algo="exact", adaptive=TRUE), notOutput="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.3, frollmax(1:4, c(2,2,2,2), adaptive=TRUE), output="frolladaptivefun: algo fast not implemented, fall back to exact")
test(6000.3001, frollmax(1:4, c(2,2,2,2), algo="fast", adaptive=TRUE), output="frolladaptivefun: algo fast not implemented, fall back to exact")
test(6000.3002, frollmax(1:4, c(2,2,2,2), algo="exact", adaptive=TRUE), notOutput="frolladaptivefun: algo fast not implemented, fall back to exact")
options(datatable.verbose=FALSE)
n = c(3,2,2,4,2,1,4,8)
x = c(7,2,3,6,3,2,6,6) # no NA
Expand Down Expand Up @@ -1022,9 +1022,9 @@ test(6000.564, frollapply(FUN=mean, 1:3, list(c(0,-1,1)), adaptive=TRUE), error=

## frollmin adaptive
options(datatable.verbose=TRUE) ## adaptive frollmin no fast algo
test(6000.6, frollmin(1:4, c(2,2,2,2), adaptive=TRUE), output="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.6001, frollmin(1:4, c(2,2,2,2), algo="fast", adaptive=TRUE), output="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.6002, frollmin(1:4, c(2,2,2,2), algo="exact", adaptive=TRUE), notOutput="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6000.6, frollmin(1:4, c(2,2,2,2), adaptive=TRUE), output="frolladaptivefun: algo fast not implemented, fall back to exact")
test(6000.6001, frollmin(1:4, c(2,2,2,2), algo="fast", adaptive=TRUE), output="frolladaptivefun: algo fast not implemented, fall back to exact")
test(6000.6002, frollmin(1:4, c(2,2,2,2), algo="exact", adaptive=TRUE), notOutput="frolladaptivefun: algo fast not implemented, fall back to exact")
options(datatable.verbose=FALSE)
n = c(3,2,2,4,2,1,4,8)
x = c(7,2,3,6,3,2,6,6) # no NA
Expand Down Expand Up @@ -1200,7 +1200,7 @@ test(6000.931, frollprod(1:3, 2), c(NA, 2, 6), output="frollprodFast: running fo
test(6000.932, frollprod(1:3, 2, align="left"), c(2, 6, NA), output="frollfun: align")
test(6000.933, frollprod(c(1,2,NA), 2), c(NA, 2, NA), output="non-finite values are present in input, re-running with extra care for NFs")
test(6000.934, frollprod(c(NA,2,3), 2), c(NA, NA, 6), output="non-finite values are present in input, skip non-finite inaware attempt and run with extra care for NFs straighaway")
test(6000.935, frollprod(1:3, c(2,2,2), adaptive=TRUE), c(NA, 2, 6), output="algo 0 not implemented, fall back to 1")
test(6000.935, frollprod(1:3, c(2,2,2), adaptive=TRUE), c(NA, 2, 6), output="algo fast not implemented, fall back to exact")
test(6000.936, frollprod(c(NA,2,3), c(2,2,2), adaptive=TRUE), c(NA, NA, 6), output="non-finite values are present in input, na.rm=FALSE and algo='exact' propagates NFs properply, no need to re-run")
options(datatable.verbose=FALSE)
# floating point overflow
Expand Down Expand Up @@ -1433,7 +1433,7 @@ test(6001.715, frollvar(1:3, 0, algo="exact"), c(NA_real_,NA_real_,NA_real_), op
test(6001.716, frollvar(c(1:2,NA), 0, algo="exact"), c(NA_real_,NA_real_,NA_real_))
test(6001.717, frollvar(c(1:2,NA), 0, algo="exact", na.rm=TRUE), c(NA_real_,NA_real_,NA_real_))
test(6001.718, frollvar(c(1:2,NA), 2), c(NA,0.5,NA), options=c("datatable.verbose"=TRUE), output="redirecting to frollvarExact")
test(6001.721, frollvar(adaptive=TRUE, 1:3, c(2,0,2)), c(NA,NA,0.5), options=c("datatable.verbose"=TRUE), output="not implemented, fall back to")
test(6001.721, frollvar(adaptive=TRUE, 1:3, c(2,0,2)), c(NA,NA,0.5), options=c("datatable.verbose"=TRUE), output="algo fast not implemented, fall back to exact")
test(6001.722, frollvar(adaptive=TRUE, 1:3, c(2,0,2), fill=99), c(99,NA,0.5))
test(6001.723, frollvar(adaptive=TRUE, c(1:2,NA), c(2,0,2)), c(NA_real_,NA_real_,NA_real_))
test(6001.724, frollvar(adaptive=TRUE, c(1:2,NA), c(2,0,2), na.rm=TRUE), c(NA_real_,NA_real_,NA_real_))
Expand Down Expand Up @@ -1492,7 +1492,7 @@ test(6001.8194, frollsd(c(NA,2:3), 2, has.nf=FALSE), c(NA,NA,sqrt(0.5)), warning
test(6001.8195, frollsd(c(NA,2:3), 2), c(NA,NA,sqrt(0.5)), options=c("datatable.verbose"=TRUE), output="skip non-finite inaware attempt and run with extra care")
test(6001.8196, frollsd(c(NA,2:3), 2, has.nf=FALSE, algo="exact"), c(NA,NA,sqrt(0.5)), warning="used but non-finite values are present in input")
test(6001.8197, frollsd(c(NA,2:3), 2, algo="exact", na.rm=TRUE), c(NA,NA,sqrt(0.5)), options=c("datatable.verbose"=TRUE), output="re-running with extra care for NF")
test(6001.8201, frollsd(adaptive=TRUE, 1:3, c(2,2,2)), c(NA,sqrt(0.5),sqrt(0.5)), options=c("datatable.verbose"=TRUE), output="frolladaptivefun: algo 0 not implemented, fall back to 1")
test(6001.8201, frollsd(adaptive=TRUE, 1:3, c(2,2,2)), c(NA,sqrt(0.5),sqrt(0.5)), options=c("datatable.verbose"=TRUE), output="frolladaptivefun: algo fast not implemented, fall back to exact")
test(6001.8202, frollsd(adaptive=TRUE, 1:3, c(2,2,2)), c(NA,sqrt(0.5),sqrt(0.5)), options=c("datatable.verbose"=TRUE), output="frolladaptivesdExact: calling sqrt(frolladaptivevarExact(...))")
test(6001.821, frollsd(adaptive=TRUE, 1:3, c(2,0,2)), c(NA,NA,sqrt(0.5)))
test(6001.822, frollsd(adaptive=TRUE, 1:3, c(2,0,2), fill=99), c(99,NA,sqrt(0.5)))
Expand Down
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