Removing spaces

Author: Omartech312

inst/tests/froll.Rraw

@@ -310,7 +310,7 @@ test(6000.0671, frollmean(c(1:2,NA,4:10), 4), c(rep(NA_real_, 6), 5.5, 6.5, 7.5,
   "frollmeanFast: non-finite values are present in input, skip non-finite unaware attempt and run with extra care for NFs straighaway",
   "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(
   "frollfunR: allocating memory for results 1x1",
   "frollfunR: .*sequentially.*single rolling computation.*",
@@ -319,7 +319,7 @@ test(6000.0672, frollmean(c(1:2,NA,4:10), 4, has.nf=FALSE), c(rep(NA_real_, 6),
   "frollmeanFast: non-finite values are present in input, skip non-finite unaware attempt and run with extra care for NFs straighaway",
   "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.*",
@@ -328,7 +328,7 @@ test(6000.0673, frollmean(c(1:2,NA,4:10), 2, has.nf=FALSE), c(NA, 1.5, NA, NA, 4
   "frollmeanFast: non-finite values are present in input, re-running with extra care for NFs",
   "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.*",
@@ -337,7 +337,7 @@ test(6000.0674, frollmean(c(1:2,NA,4:10), 4, align="center"), c(rep(NA_real_, 4)
   "frollfun: align 0, shift answer by -2",
   "frollfun: processing fun MEAN algo fast took.*",
   "frollfunR: processing.*took.*"
-))  
+))
 options(datatable.verbose=FALSE)
 
 #### fill constant
@@ -438,7 +438,7 @@ test(6000.1196, frollmean(c(1:5,NA), 1:6, algo="exact", na.rm=TRUE, adaptive=TRU
   "frolladaptivemeanExact: non-finite values are present in input, re-running with extra care for NFs",
   "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",
@@ -676,7 +676,7 @@ test(6000.171, frollmean(x, n), output=c(
   "frollfunR: 1:",
   "frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
   "frollfun: processing fun MEAN algo fast took.*",
-  "frollfunR: processing.*took.*"))  
+  "frollfunR: processing.*took.*"))
 test(6000.172, frollmean(list(x, x+1), n), output=c(
   "frollfunR: allocating memory for results 2x1",
   "frollfunR: .*in parallel.*",
@@ -686,7 +686,7 @@ test(6000.172, frollmean(list(x, x+1), n), output=c(
   "frollfunR: 2:",
   "frollmeanFast: running for input length 10, window 3, hasnf 0, narm 0",
   "frollfun: processing fun MEAN algo fast took.*",
-  "frollfunR: processing.*took.*"))  
+  "frollfunR: processing.*took.*"))
 test(6000.173, frollmean(x, c(n, n+1)), output=c(
   "frollfunR: allocating memory for results 1x2",
   "frollfunR: .*in parallel.*",
@@ -696,7 +696,7 @@ test(6000.173, frollmean(x, c(n, n+1)), output=c(
   "frollfunR: 2:",
   "frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
   "frollfun: processing fun MEAN algo fast took.*",
-  "frollfunR: processing.*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.*",
@@ -712,45 +712,45 @@ test(6000.174, frollmean(list(x, x+1), c(n, n+1)), output=c(
   "frollfunR: 4:",
   "frollmeanFast: running for input length 10, window 4, hasnf 0, narm 0",
   "frollfun: processing fun MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo exact took.*",
-  "frollfunR: processing.*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 MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo exact took.*",
-  "frollfunR: processing.*took.*"))  
+  "frollfunR: processing.*took.*"))
 
 x[8] = NA
 test(6000.180, frollmean(x, n), output=c(
@@ -760,31 +760,31 @@ test(6000.180, frollmean(x, n), output=c(
   "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 MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo exact took.*",
-  "frollfunR: processing.*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 MEAN algo fast took.*",
-  "frollfunR: processing.*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 MEAN algo exact took.*",
-  "frollfunR: processing.*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(
@@ -794,7 +794,7 @@ test(6000.184, frollmean(d[,1], 3, algo="exact"), output=c(
   "frollmeanExact: running in parallel for input length 10, window 3, hasnf 0, narm 0",
   "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.*",
@@ -811,7 +811,7 @@ test(6000.185, frollmean(d, 3:4, algo="exact"), output=c(
   "frollmeanExact: running in parallel for input length 10, window 4, hasnf 0, narm 0",
   "frollfun: processing fun MEAN algo exact took.*",
   "frollfunR: processing.*took.*"
-))  
+))
 options(datatable.verbose=FALSE)
 
 ## test warnings
@@ -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 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")  
+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 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")  
+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 fast not implemented, fall back to exact")  
+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="algo fast not implemented, fall back to exact")  
+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 fast not implemented, fall back to exact")  
+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)))