R Under development (unstable) (2026-03-09 r89583 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> 
> Wild <- function(x) { 		## 'Wild' function, global minimum at about -15.81515
+     sum(10 * sin(0.3 * x) * sin(1.3 * x^2) + 0.00001 * x^4 + 0.2 * x + 80)/length(x)
+ }
> 
> Rastrigin <- function(x) {
+     sum(x+2 - 10 * cos(2*pi*x)) + 20
+ }
> 
> Genrose <- function(x, a = 1, b = 100) { 	## One generalization of the Rosenbrock banana valley function (n parameters)
+     n <- length(x)
+     1.0 + sum (b * (x[-n]^2 - x[-1])^2 + (x[-1] - a)^2)
+ }
> 
> maxIt <- 25         		# not excessive but so that we get some run-time on simple problems
> 
> haveDEoptim <- requireNamespace("DEoptim", quietly=TRUE)
> 
> suppressMessages({
+     if (haveDEoptim) {
+         library(DEoptim) 	# the original, currently 2.0.7
+     }
+     library(RcppDE) 		# the contender
+ })
> 
> basicDE <- function(n, maxIt, fun, ...) DEoptim::DEoptim(fn=fun, lower=rep(-25, n), upper=rep(25, n),
+                                                          control=list(NP=10*n, itermax=maxIt, trace=FALSE),
+                                                          ...)#, bs=TRUE))
> cppDE <- function(n, maxIt, fun, ...) RcppDE::DEoptim(fn=fun, lower=rep(-25, n), upper=rep(25, n),
+                                                       control=list(NP=10*n, itermax=maxIt, trace=FALSE),
+                                                       ...)#, bs=TRUE))
> 
> if (haveDEoptim) {
+     set.seed(42)
+     valBasic <- basicDE(5, maxIt, function(...) Rastrigin(...))
+     set.seed(42)
+     valCpp <- cppDE(5, maxIt, function(...) Rastrigin(...))
+     ##stopifnot( all.equal(valBasic, valCpp) )
+ }
> 
> runPair <- function(n, maxIt, fun, funname, ...) {
+     gc()
+     set.seed(42)
+     bt <- system.time(invisible(ores <- basicDE(n, maxIt, fun, ...)))[3]
+ 
+     gc()
+     set.seed(42)
+     xptr <- RcppDE:::putFunPtrInXPtr(funname)
+     ct <- system.time(invisible(cres <- cppDE(n, maxIt, xptr, ...)))[3]
+ 
+     #stopifnot(all.equal(ores, cres))
+ 
+     gc()
+     set.seed(42)
+     rt <- system.time(invisible(rres <- cppDE(n, maxIt, fun, ...)))[3]
+ 
+     ##stopifnot(all.equal(ores, rres))
+ 
+     return(data.frame(DEoptim=bt, RcppDEc=ct, RcppDEr=rt))
+ }
> 
> if (haveDEoptim) {
+ 
+     cat("# At", format(Sys.time()), "\n")
+     options(width=120)
+ 
+     reps <- c(5, 10, 20, 50)
+ 
+     res <- rbind(do.call(rbind, lapply(reps, runPair, maxIt, function(...) Rastrigin(...), "rastrigin")),
+                  do.call(rbind, lapply(reps, runPair, maxIt, function(...) Wild(...), "wild")),
+                  do.call(rbind, lapply(reps, runPair, maxIt, function(...) Genrose(...), "genrose", a = 1, b = 100))
+                  )
+     res <- rbind(res, colMeans(res))
+ 
+     rownames(res) <- c(paste("Rastrigin", reps, sep=""),
+                        paste("Wild", reps, sep=""),
+                        paste("Genrose", reps, sep=""),
+                        "MEANS")
+ 
+     res$ratioRcppCompToBasic <- res[,2]/res[,1]
+     res$pctGainOfRcppComp <- (1-res[,2]/res[,1])*100
+     ##res$netSpeedUpC <- res[,1]/res[,2]
+ 
+     res$ratioRcppRToBasic <- res[,3]/res[,1]
+     res$pctGainOfRcppR <- round((1-res[,3]/res[,1])*100, digits=3)
+     ##res$netSpeedUpR <- res[,1]/res[,3]
+ 
+ 
+     print(res)
+     cat("# Done", format(Sys.time()), "\n")
+ }
# At 2026-03-10 19:02:28 
               DEoptim RcppDEc    RcppDEr ratioRcppCompToBasic pctGainOfRcppComp ratioRcppRToBasic pctGainOfRcppR
Rastrigin5  0.02000000  0.0100 0.00000000            0.5000000          50.00000         0.0000000        100.000
Rastrigin10 0.02000000  0.0000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Rastrigin20 0.05000000  0.0100 0.03000000            0.2000000          80.00000         0.6000000         40.000
Rastrigin50 0.17000000  0.0600 0.08000000            0.3529412          64.70588         0.4705882         52.941
Wild5       0.02000000  0.0000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Wild10      0.04000000  0.0000 0.02000000            0.0000000         100.00000         0.5000000         50.000
Wild20      0.07000000  0.0400 0.05000000            0.5714286          42.85714         0.7142857         28.571
Wild50      0.38000000  0.1300 0.27000000            0.3421053          65.78947         0.7105263         28.947
Genrose5    0.01000000  0.0000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Genrose10   0.02000000  0.0100 0.02000000            0.5000000          50.00000         1.0000000          0.000
Genrose20   0.04000000  0.0000 0.05000000            0.0000000         100.00000         1.2500000        -25.000
Genrose50   0.25000000  0.0100 0.24000000            0.0400000          96.00000         0.9600000          4.000
MEANS       0.09083333  0.0225 0.06333333            0.2477064          75.22936         0.6972477         30.275
# Done 2026-03-10 19:02:34 
> 
> proc.time()
   user  system elapsed 
   5.85    0.37    6.26