Nothing
inst/doc/RcppDE.R
In RcppDE: Global Optimization by Differential Evolution in C++
### R code from vignette source 'RcppDE.Rnw'
###################################################
### code chunk number 1: prelim
###################################################
options(width=50)
library(lattice)
library(RcppDE)
RcppDE.version <- packageDescription("RcppDE")$Version
RcppDE.date <- packageDescription("RcppDE")$Date
now.date <- strftime(Sys.Date(), "%B %d, %Y")
# create figures/ if not present
if ( ! (file.exists("figures") && file.info("figures")[["isdir"]]) ) dir.create("figures")
###################################################
### code chunk number 2: smallRes
###################################################
## # small benchmark at SVN 2419M
## # At 2010-11-08 06:42:29.018531
smallLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin5 0.10912 0.099875 0.91523 8.4765 1.0926
Rastrigin10 0.23738 0.214875 0.90521 9.4787 1.1047
Rastrigin20 0.55587 0.501500 0.90218 9.7819 1.1084
Wild5 0.18288 0.171875 0.93985 6.0150 1.0640
Wild10 0.40912 0.391125 0.95600 4.3996 1.0460
Wild20 1.04513 0.987375 0.94474 5.5257 1.0585
Genrose5 0.18913 0.179250 0.94779 5.2214 1.0551
Genrose10 0.39538 0.374625 0.94752 5.2482 1.0554
Genrose20 0.90050 0.848375 0.94212 5.7885 1.0614
"
## MEANS 0.44717 0.418764 0.93648 6.3517 1.0678
## # Done 2010-11-08 06:43:50.88171
con <- textConnection(smallLines)
smallData <- read.table(con, header=TRUE, sep="")
close(con)
sb <- trellis.par.get("strip.background")
sb[["col"]][1:2] <- c("gray80","gray90")
trellis.par.set("strip.background", sb)
# dput(brewer.pal(7, "Set1"))
.cols <- c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
"#FF7F00", "#FFF33", "#A65628")[-6]
ss <- trellis.par.get("superpose.symbol")
ss[["col"]][1:6] <- .cols
ss[["cex"]] <- rep(1.0, 7)
ss[["pch"]] <- rep(19, 7)
ss[["alpha"]] <- rep(0.75, 7)
trellis.par.set("superpose.symbol", ss)
smallWide <- data.frame(timeInSeconds=c(smallData[,1,drop=TRUE], smallData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(5,10,20), 6)
smallWide$fun <- factor(smallWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=smallWide, layout=c(1,3),
xlab="Time in seconds for 5, 10 and 20 parameter problems, using logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(0.1, 0.2, 0.4, 0.6, 0.8, 1.0), labels=c(0.1, 0.2, 0.4, 0.6, 0.8, 1.0))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
###################################################
### code chunk number 3: largeRes
###################################################
## # big benchmark at SVN 2419M
## # At 2010-11-08 06:43:51.422299
largeLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin50 1.770 1.575 0.88983 11.0169 1.1238
Rastrigin100 4.794 4.258 0.88819 11.1806 1.1259
Rastrigin200 14.840 12.472 0.84043 15.9569 1.1899
Wild50 3.692 3.558 0.96371 3.6295 1.0377
Wild100 11.127 10.646 0.95677 4.3228 1.0452
Wild200 38.026 35.755 0.94028 5.9722 1.0635
Genrose50 2.587 2.414 0.93313 6.6873 1.0717
Genrose100 6.252 5.739 0.91795 8.2054 1.0894
Genrose200 17.058 15.147 0.88797 11.2030 1.1262
"
## MEANS 11.127 10.174 0.91431 8.5695 1.0937
## # Done 2010-11-08 06:47:03.810348
con <- textConnection(largeLines)
largeData <- read.table(con, header=TRUE, sep="")
close(con)
largeWide <- data.frame(timeInSeconds=c(largeData[,1,drop=TRUE], largeData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(50,100,200), 6)
largeWide$fun <- factor(largeWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=largeWide, layout=c(1,3),
xlab="Time in seconds for 50, 100 and 200 parameter problems, using logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(1, 2, 5, 10, 20, 30), labels=c(1, 2, 5, 10, 20, 30))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
###################################################
### code chunk number 4: compiledRes
###################################################
## # compiled benchmark at SVN 2419:2421M
## # At 2010-11-08 06:48:42.56918
compiledLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin50 1.781 0.6090 0.34194 65.806 2.9245
Rastrigin100 4.807 2.0940 0.43561 56.439 2.2956
Rastrigin200 14.572 7.5000 0.51469 48.531 1.9429
Wild50 3.748 0.9500 0.25347 74.653 3.9453
Wild100 11.268 3.3160 0.29428 70.572 3.3981
Wild200 37.225 12.4120 0.33343 66.657 2.9991
Genrose50 2.667 0.2710 0.10161 89.839 9.8413
Genrose100 6.498 0.7190 0.11065 88.935 9.0376
Genrose200 17.471 1.9830 0.11350 88.650 8.8104
"
## MEANS 11.115 3.3171 0.29843 70.157 3.3509
## # Done 2010-11-08 06:50:53.195003
con <- textConnection(compiledLines)
compiledData <- read.table(con, header=TRUE, sep="")
close(con)
compiledWide <- data.frame(timeInSeconds=c(compiledData[,1,drop=TRUE], compiledData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(50,100,200), 6)
compiledWide$fun <- factor(compiledWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=compiledWide, layout=c(1,3),
xlab="Time in sec. for 50, 100 and 200 parameter problems, compiled objective function, logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(0.5, 1, 2, 5, 10, 20, 30), labels=c(0.5, 1, 2, 5, 10, 20, 30))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
Try the RcppDE package in your browser
Any scripts or data that you put into this service are public.
RcppDE documentation built on Dec. 28, 2022, 1:12 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
### R code from vignette source 'RcppDE.Rnw'
###################################################
### code chunk number 1: prelim
###################################################
options(width=50)
library(lattice)
library(RcppDE)
RcppDE.version <- packageDescription("RcppDE")$Version
RcppDE.date <- packageDescription("RcppDE")$Date
now.date <- strftime(Sys.Date(), "%B %d, %Y")
# create figures/ if not present
if ( ! (file.exists("figures") && file.info("figures")[["isdir"]]) ) dir.create("figures")
###################################################
### code chunk number 2: smallRes
###################################################
## # small benchmark at SVN 2419M
## # At 2010-11-08 06:42:29.018531
smallLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin5 0.10912 0.099875 0.91523 8.4765 1.0926
Rastrigin10 0.23738 0.214875 0.90521 9.4787 1.1047
Rastrigin20 0.55587 0.501500 0.90218 9.7819 1.1084
Wild5 0.18288 0.171875 0.93985 6.0150 1.0640
Wild10 0.40912 0.391125 0.95600 4.3996 1.0460
Wild20 1.04513 0.987375 0.94474 5.5257 1.0585
Genrose5 0.18913 0.179250 0.94779 5.2214 1.0551
Genrose10 0.39538 0.374625 0.94752 5.2482 1.0554
Genrose20 0.90050 0.848375 0.94212 5.7885 1.0614
"
## MEANS 0.44717 0.418764 0.93648 6.3517 1.0678
## # Done 2010-11-08 06:43:50.88171
con <- textConnection(smallLines)
smallData <- read.table(con, header=TRUE, sep="")
close(con)
sb <- trellis.par.get("strip.background")
sb[["col"]][1:2] <- c("gray80","gray90")
trellis.par.set("strip.background", sb)
# dput(brewer.pal(7, "Set1"))
.cols <- c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
"#FF7F00", "#FFF33", "#A65628")[-6]
ss <- trellis.par.get("superpose.symbol")
ss[["col"]][1:6] <- .cols
ss[["cex"]] <- rep(1.0, 7)
ss[["pch"]] <- rep(19, 7)
ss[["alpha"]] <- rep(0.75, 7)
trellis.par.set("superpose.symbol", ss)
smallWide <- data.frame(timeInSeconds=c(smallData[,1,drop=TRUE], smallData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(5,10,20), 6)
smallWide$fun <- factor(smallWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=smallWide, layout=c(1,3),
xlab="Time in seconds for 5, 10 and 20 parameter problems, using logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(0.1, 0.2, 0.4, 0.6, 0.8, 1.0), labels=c(0.1, 0.2, 0.4, 0.6, 0.8, 1.0))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
###################################################
### code chunk number 3: largeRes
###################################################
## # big benchmark at SVN 2419M
## # At 2010-11-08 06:43:51.422299
largeLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin50 1.770 1.575 0.88983 11.0169 1.1238
Rastrigin100 4.794 4.258 0.88819 11.1806 1.1259
Rastrigin200 14.840 12.472 0.84043 15.9569 1.1899
Wild50 3.692 3.558 0.96371 3.6295 1.0377
Wild100 11.127 10.646 0.95677 4.3228 1.0452
Wild200 38.026 35.755 0.94028 5.9722 1.0635
Genrose50 2.587 2.414 0.93313 6.6873 1.0717
Genrose100 6.252 5.739 0.91795 8.2054 1.0894
Genrose200 17.058 15.147 0.88797 11.2030 1.1262
"
## MEANS 11.127 10.174 0.91431 8.5695 1.0937
## # Done 2010-11-08 06:47:03.810348
con <- textConnection(largeLines)
largeData <- read.table(con, header=TRUE, sep="")
close(con)
largeWide <- data.frame(timeInSeconds=c(largeData[,1,drop=TRUE], largeData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(50,100,200), 6)
largeWide$fun <- factor(largeWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=largeWide, layout=c(1,3),
xlab="Time in seconds for 50, 100 and 200 parameter problems, using logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(1, 2, 5, 10, 20, 30), labels=c(1, 2, 5, 10, 20, 30))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
###################################################
### code chunk number 4: compiledRes
###################################################
## # compiled benchmark at SVN 2419:2421M
## # At 2010-11-08 06:48:42.56918
compiledLines <- "
DEoptim RcppDE ratioRcppToBasic pctGainOfRcpp netSpeedUp
Rastrigin50 1.781 0.6090 0.34194 65.806 2.9245
Rastrigin100 4.807 2.0940 0.43561 56.439 2.2956
Rastrigin200 14.572 7.5000 0.51469 48.531 1.9429
Wild50 3.748 0.9500 0.25347 74.653 3.9453
Wild100 11.268 3.3160 0.29428 70.572 3.3981
Wild200 37.225 12.4120 0.33343 66.657 2.9991
Genrose50 2.667 0.2710 0.10161 89.839 9.8413
Genrose100 6.498 0.7190 0.11065 88.935 9.0376
Genrose200 17.471 1.9830 0.11350 88.650 8.8104
"
## MEANS 11.115 3.3171 0.29843 70.157 3.3509
## # Done 2010-11-08 06:50:53.195003
con <- textConnection(compiledLines)
compiledData <- read.table(con, header=TRUE, sep="")
close(con)
compiledWide <- data.frame(timeInSeconds=c(compiledData[,1,drop=TRUE], compiledData[,2,drop=TRUE]),
pkg=rep(c("DEoptim", "RcppDE"), each=9),
fun=rep(rep(c("Rastrigin", "Wild", "Genrose"), each=3), 2),
n=c(50,100,200), 6)
compiledWide$fun <- factor(compiledWide$fun, levels=c("Rastrigin", "Genrose", "Wild"))
print(dotplot(as.factor(n) ~ timeInSeconds | fun, group=pkg, data=compiledWide, layout=c(1,3),
xlab="Time in sec. for 50, 100 and 200 parameter problems, compiled objective function, logarithmic axis", ylab="",
scales=list(x=list(log=TRUE,at=c(0.5, 1, 2, 5, 10, 20, 30), labels=c(0.5, 1, 2, 5, 10, 20, 30))),
key=simpleKey(text=c("DEoptim","RcppDE"), space="top")))
Try the RcppDE package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.