R Under development (unstable) (2025-02-17 r87739 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 
> 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 2025-02-19 00:49:03 
               DEoptim    RcppDEc    RcppDEr ratioRcppCompToBasic pctGainOfRcppComp ratioRcppRToBasic pctGainOfRcppR
Rastrigin5  0.01000000 0.00000000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Rastrigin10 0.02000000 0.00000000 0.01000000            0.0000000         100.00000         0.5000000         50.000
Rastrigin20 0.02000000 0.00000000 0.03000000            0.0000000         100.00000         1.5000000        -50.000
Rastrigin50 0.11000000 0.04000000 0.08000000            0.3636364          63.63636         0.7272727         27.273
Wild5       0.02000000 0.00000000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Wild10      0.02000000 0.00000000 0.01000000            0.0000000         100.00000         0.5000000         50.000
Wild20      0.05000000 0.01000000 0.03000000            0.2000000          80.00000         0.6000000         40.000
Wild50      0.28000000 0.08000000 0.18000000            0.2857143          71.42857         0.6428571         35.714
Genrose5    0.01000000 0.00000000 0.00000000            0.0000000         100.00000         0.0000000        100.000
Genrose10   0.00000000 0.00000000 0.01000000                  NaN               NaN               Inf           -Inf
Genrose20   0.03000000 0.00000000 0.03000000            0.0000000         100.00000         1.0000000          0.000
Genrose50   0.14000000 0.00000000 0.11000000            0.0000000         100.00000         0.7857143         21.429
MEANS       0.05916667 0.01083333 0.04083333            0.1830986          81.69014         0.6901408         30.986
# Done 2025-02-19 00:49:06 
> 
> proc.time()
   user  system elapsed 
   3.53    0.26    3.73