Improved verbose messages in rolling functions frolladaptivefun and frollfun

NEWS.md

@@ -60,6 +60,8 @@
 
 6. Enhanced tests for OpenMP support, detecting incompatibilities such as R-bundled runtime _vs._ newer Xcode and testing for a manually installed runtime from <https://mac.r-project.org/openmp>, [#6622](https://github.com/Rdatatable/data.table/issues/6622). Thanks to @dvg-p4 for initial report and testing, @twitched for the pointers, @tdhock and @aitap for the fix.
 
+7. Verbose outputs from `frolladaptivefun()` and `frollfun()` are now clearer and more user friendly [#7021](https://github.com/Rdatatable/data.table/issues/7021). Thanks to @Omartech312, @aidengseay, @kkarissa, and @heb229 for the implementation, to @ben-schwen for the review, and to @jangorecki for the extensive guidance and review.
+
 ## data.table [v1.18.4](https://github.com/Rdatatable/data.table/milestone/45) (6 May 2026)
 
 ### BUG FIXES

inst/tests/froll.Rraw

@@ -308,7 +308,7 @@ 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.*"
 ))
 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(
@@ -317,7 +317,7 @@ test(6000.0672, frollmean(c(1:2,NA,4:10), 4, has.nf=FALSE), c(rep(NA_real_, 6),
   "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")
 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(
@@ -326,7 +326,7 @@ test(6000.0673, frollmean(c(1:2,NA,4:10), 2, has.nf=FALSE), c(NA, 1.5, NA, NA, 4
   "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")
 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(
@@ -335,7 +335,7 @@ test(6000.0674, frollmean(c(1:2,NA,4:10), 4, align="center"), c(rep(NA_real_, 4)
   "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)
@@ -436,7 +436,7 @@ 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
@@ -446,7 +446,7 @@ test(6000.1197, frollmean(c(1:5,NA), 2, algo="exact", na.rm=TRUE), output=c(
   "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)
@@ -675,81 +675,81 @@ 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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "frolladaptivefun: processing fun MEAN algo exact took.*",
   "frollfunR: processing.*took.*"))
 
 x[8] = NA
@@ -759,31 +759,31 @@ 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.*",
+  "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.*",
+  "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.*",
+  "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.*",
+  "frolladaptivefun: processing fun MEAN algo exact took.*",
   "frollfunR: processing.*took.*"))
 
 d = as.data.table(list(1:10/2, 10:1/4))
@@ -792,24 +792,24 @@ test(6000.184, frollmean(d[,1], 3, algo="exact"), output=c(
   "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)
@@ -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
@@ -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
@@ -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
@@ -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_))
@@ -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)))

src/data.table.h

@@ -259,6 +259,7 @@ typedef enum { // adding rolling functions here and in frollfunR in frollR.c
   VAR = 6,
   SD = 7
 } rollfun_t;
+extern const char *const rfunNames[]; // Array of roll function names defined in froll.c
 // froll.c
 void frollfun(rollfun_t rfun, unsigned int algo, const double *x, uint64_t nx, ans_t *ans, int k, int align, double fill, bool narm, int hasnf, bool verbose, bool par);
 void frollmeanFast(const double *x, uint64_t nx, ans_t *ans, int k, double fill, bool narm, int hasnf, bool verbose);

src/froll.c

@@ -1,5 +1,7 @@
 #include "data.table.h"
 
+const char *const rfunNames[] = {
+  "MEAN", "SUM", "MAX", "MIN", "PROD", "MEDIAN", "VAR", "SD"}; //constant definition of froll functions
 /*
   OpenMP is used here to parallelize the loops in most of the
     implementations of rolling functions.
@@ -104,7 +106,7 @@ void frollfun(rollfun_t rfun, unsigned int algo, const double *x, uint64_t nx, a
     }
   }
   if (verbose)
-    snprintf(end(ans->message[0]), 500, _("%s: processing fun %d algo %u took %.3fs\n"), __func__, rfun, algo, omp_get_wtime()-tic);
+    snprintf(end(ans->message[0]), 500, _("%s: processing fun %s algo %s took %.3fs\n"), __func__, rfunNames[rfun], (algo == 0) ? "fast" : "exact", omp_get_wtime()-tic);
 }
 
 #undef SUM_WINDOW_STEP_FRONT