R/ecdf-plot.R
In warbarbye/cecs-benchmark: Benchmarking optimization methods
Defines functions
ecdfIEEE
combinedPlot
plotCECline
plotAllSingle
plotEcdfPresentation
library(ggplot2)
ecdfIEEE<- function(n,f_from,f_to){
N <- n
F_from <- f_from
F_to <- f_to
print(paste("Dimension: ",n,sep=''))
#des_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMADE-BBComp5 HistSize=3sqrt(N) init(-80,80) FINALTEST/M/"
rb_ipop_cma_es_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/paper ID E-17343/RB-IPOP-CMA-ES/"
cmaes_pure = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES/M/"
cmaes_4N = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES L=4N/M/"
des_pathv2 = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/DESv2/DES - tol_v2/M/"
jsopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17315/jSO/"
lshadeSpacma_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17051/LSHADE_SPACMA/"
#cmaesNos_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES noSigma/M/"
ebopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/EBOwithCMAR/data for email/"
#idepath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17322/IDEbestNsize/"
#ppsopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/paper ID E-17447/cec2017PPSO/"
#mmoedpath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17321/Multi-method based Orthogonal Experimental Design Algorithm for Solving CEC2017 Competition Problems results/"
#dyypopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17543/DYYPO/"
#tlboflpath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17544/TLBO-FL/"
#moscec2012path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_cec2012/"
#moscec2013path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_cec2013/"
#mossoco2011path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_soco2011/"
ecdfValues <- list()
budgetSteps <- c(0.01, 0.02, 0.03, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)*log10(10000)
#colors_ <- rainbow(16)
#colors_[6] <- rainbow(50)[50]
#colors_[3] <- colors_[16]
#colors_ <- c(rep("black",2),rep("grey",12))
#linetype <- c(c(1:6),c(1:6),c(1:6))
#plotchar <- c( seq(15,15+10,1),8,13,14,13)
ecdfMaxSucess <- 0
#resultsDES <- list()
resultsRB_IPOP_CMA_ES <- list()
resultsCmaes_pure <- list()
resultsCmaes_4n <- list()
resultsDESv2 <- list()
resultsjso <- list()
resultslshadeSpacma <- list()
#resultsCmaesNos <- list()
resultsEbo <- list()
resultsIDE <- list()
resultsPPSO <- list()
resultsMMOED <- list()
resultsDYYPO <- list()
resultsTLBOFL <- list()
resulsMOSCEC2012 <- list()
resulsMOSCEC2013 <- list()
resulsMOSSOCO2011 <- list()
for(p in 1:30){
#resultsDES[[p]] <- read.table(file = paste(des_path,"DES_",p,"_",N,".txt",sep=""),sep = ",")
resultsRB_IPOP_CMA_ES[[p]] <- read.table(file = paste(rb_ipop_cma_es_path,"RB-IPOP-CMA-ES_",p,"_",N,".txt",sep=""),sep = " ")
resultsCmaes_pure[[p]] <- read.table(file = paste(cmaes_pure,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
resultsDESv2[[p]] <- read.table(file = paste(des_pathv2,"DES_",p,"_",N,".txt",sep=""),sep = ",")
resultsjso[[p]] <- read.table(file = paste(jsopath,"jSO_",p,"_",N,".txt",sep=""))
resultslshadeSpacma[[p]] <- read.table(file = paste(lshadeSpacma_path,"LSHADE_SPACMA_",p,"_",N,".txt",sep=""))
#resultsCmaesNos[[p]] <- read.table(file = paste(cmaesNos_path,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
resultsEbo[[p]] <- read.table(file = paste(ebopath,"EBOwithCMAR_",p,"_",N,".dat",sep=""))
resultsCmaes_4n[[p]] <- read.table(file = paste(cmaes_4N,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
#resultsIDE[[p]] <- read.table(file = paste(idepath,"IDEbestNsize_",N,"_",p,".txt",sep=""))
#resultsPPSO[[p]] <- read.table(file = paste(ppsopath,"PPSO_",p,"_",N,".txt",sep=""))
#resultsMMOED[[p]] <- read.table(file = paste(mmoedpath,"MM_OED_",p,"_",N,".txt",sep=""))
#resultsDYYPO[[p]] <- read.table(file = paste(dyypopath,"DYYPO_",p,"_",N,".txt",sep=""))
#resultsTLBOFL[[p]] <- read.table(file = paste(tlboflpath,"TLBO-FL_",p,"_",N,".txt",sep=""))
#resulsMOSCEC2012[[p]] <- read.table(file = paste(moscec2012path,"MOS-CEC2012_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
#resulsMOSCEC2013[[p]] <- read.table(file = paste(moscec2013path,"MOS-CEC2013_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
#resulsMOSSOCO2011[[p]] <- read.table(file = paste(mossoco2011path,"MOS-SOCO2011_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
ecdfValues[[p]] <- rev(c(1 %o% (10)^(0.2*((log10(max(min(
#min(resultsDES[[p]][14,]),
min(resultsRB_IPOP_CMA_ES[[p]][14,]),
min(resultsCmaes_pure[[p]][14,]),
min(resultsDESv2[[p]][14,]),
min(resultsjso[[p]][14,]),
min(resultslshadeSpacma[[p]][14,]),
#min(resultsCmaesNos[[p]][14,]),
min(resultsEbo[[p]][14,]),
min(resultsCmaes_4n[[p]][14,])
#min(resultsIDE[[p]][14,]),
#min(resultsPPSO[[p]][14,]),
#min(resultsMMOED[[p]][14,]),
#min(resultsDYYPO[[p]][14,]),
#min(resultsTLBOFL[[p]][14,]),
#min(resulsMOSCEC2012[[p]][14,]),
#min(resulsMOSCEC2013[[p]][14,]),
#min(resulsMOSSOCO2011[[p]][14,])
),10^-8) )/0.2):(log10(max(
#max(resultsDES[[p]][1,]),
max(resultsRB_IPOP_CMA_ES[[p]][1,]),
max(resultsCmaes_pure[[p]][1,]),
max(resultsDESv2[[p]][1,]),
max(resultsjso[[p]][1,]),
max(resultslshadeSpacma[[p]][1,]),
#max(resultsCmaesNos[[p]][1,]),
max(resultsEbo[[p]][1,]),
max(resultsCmaes_4n[[p]][1,])
#max(resultsIDE[[p]][1,]),
#max(resultsPPSO[[p]][1,]),
#max(resultsMMOED[[p]][1,]),
#max(resultsDYYPO[[p]][1,]),
#max(resultsTLBOFL[[p]][1,]),
#max(resulsMOSCEC2012[[p]][1,]),
#max(resulsMOSCEC2013[[p]][1,]),
#max(resulsMOSSOCO2011[[p]][1,])
) )/0.2) ))))
}
#minCountDES <- rep(0,length(budgetSteps))
minCountRB_IPOP_CMA_ES <- rep(0,length(budgetSteps))
minCountCmaes_pure <- rep(0,length(budgetSteps))
minCountDESv2 <- rep(0,length(budgetSteps))
minCountjso <- rep(0,length(budgetSteps))
minCountshadeSpacma <- rep(0,length(budgetSteps))
#minCountCmaes_nos <- rep(0,length(budgetSteps))
minCountEbo <- rep(0,length(budgetSteps))
minCountCmaes_4N <- rep(0,length(budgetSteps))
minCountIde <- rep(0,length(budgetSteps))
minCountPpso <- rep(0,length(budgetSteps))
minCountMmoed <- rep(0,length(budgetSteps))
minCountDyypo <- rep(0,length(budgetSteps))
minCountTlbofl <- rep(0,length(budgetSteps))
minCountMosCec2012 <- rep(0,length(budgetSteps))
minCountMosCec2013 <- rep(0,length(budgetSteps))
minCountMosSoco2011 <- rep(0,length(budgetSteps))
for(p in F_from:F_to){
print(paste("Calculating for function: ",p))
for(b in 1:length(budgetSteps)){
for(e in 1:length(ecdfValues[[p]])){
#minCountDES[b] <- minCountDES[b] + sum(resultsDES[[p]][b,]<ecdfValues[[p]][e])
minCountRB_IPOP_CMA_ES[b] <- minCountRB_IPOP_CMA_ES[b] + sum(resultsRB_IPOP_CMA_ES[[p]][b,]<ecdfValues[[p]][e])
minCountCmaes_pure[b] <- minCountCmaes_pure[b] + sum(resultsCmaes_pure[[p]][b,]<ecdfValues[[p]][e])
minCountDESv2[b] <- minCountDESv2[b] + sum(resultsDESv2[[p]][b,]<ecdfValues[[p]][e])
minCountjso[b] <- minCountjso[b] + sum(resultsjso[[p]][b,]<ecdfValues[[p]][e])
minCountshadeSpacma[b] <- minCountshadeSpacma[b] + sum(resultslshadeSpacma[[p]][b,]<ecdfValues[[p]][e])
#minCountCmaes_nos[b] <- minCountCmaes_nos[b] + sum(resultsCmaesNos[[p]][b,]<ecdfValues[[p]][e])
minCountEbo[b] <- minCountEbo[b] + sum(resultsEbo[[p]][b,]<ecdfValues[[p]][e])
minCountCmaes_4N[b] <- minCountCmaes_4N[b] + sum(resultsCmaes_4n[[p]][b,]<ecdfValues[[p]][e])
#minCountIde[b] <- minCountIde[b] + sum(resultsIDE[[p]][b,]<ecdfValues[[p]][e])
#minCountPpso[b] <- minCountPpso[b] + sum(resultsPPSO[[p]][b,]<ecdfValues[[p]][e])
#minCountMmoed[b] <- minCountMmoed[b] + sum(resultsMMOED[[p]][b,]<ecdfValues[[p]][e])
#minCountDyypo[b] <- minCountDyypo[b] + sum(resultsDYYPO[[p]][b,]<ecdfValues[[p]][e])
#minCountTlbofl[b] <- minCountTlbofl[b] + sum(resultsTLBOFL[[p]][b,]<ecdfValues[[p]][e])
#minCountMosCec2012[b] <- minCountMosCec2012[b] + sum(resulsMOSCEC2012[[p]][b,]<ecdfValues[[p]][e])
#minCountMosCec2013[b] <- minCountMosCec2013[b] + sum(resulsMOSCEC2013[[p]][b,]<ecdfValues[[p]][e])
#minCountMosSoco2011[b] <- minCountMosSoco2011[b] + sum(resulsMOSSOCO2011[[p]][b,]<ecdfValues[[p]][e])
}
}
ecdfMaxSucess <- ecdfMaxSucess + length(ecdfValues[[p]])*51
}
# All single plot
isYaxt <- "s"
isXaxt <- "s"
# Line plot
#isXaxt <- "s"
#isYaxt <- if(N==10) "s" else "n"
# Combined plot
#isYaxt <- if(N==10) "s" else "n"
#isXaxt <- if(F_from==21) "s" else "n"
#setEPS()
# postscript( paste("Problems",F_from,"-",F_to,",N=",N,".eps",sep=""), width = 15, height = 15)
#xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs",
rplot <- plot(budgetSteps,minCountjso/(ecdfMaxSucess),xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs",ylim=c(0, 1),type="b", lwd=2,lty=linetype[4], col=colors_[4], pch=plotchar[4], xaxt=isXaxt, yaxt=isYaxt, cex.axis=1.5)
lines(budgetSteps,minCountshadeSpacma/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[5], col=colors_[5], pch=plotchar[5])
lines(budgetSteps,minCountEbo/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[6], col=colors_[6], pch=plotchar[6])
#lines(budgetSteps,minCountIde/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[7], col=colors_[7], pch=plotchar[7])
#lines(budgetSteps,minCountPpso/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[8], col=colors_[8], pch=plotchar[8])
#lines(budgetSteps,minCountMmoed/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[9], col=colors_[9], pch=plotchar[9])
#lines(budgetSteps,minCountDyypo/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[10], col=colors_[10], pch=plotchar[10])
#lines(budgetSteps,minCountTlbofl/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[11], col=colors_[11], pch=plotchar[11])
#lines(budgetSteps,minCountMosCec2012/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[12], col=colors_[12], pch=plotchar[12])
#lines(budgetSteps,minCountMosCec2013/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[13], col=colors_[13], pch=plotchar[13])
#lines(budgetSteps,minCountMosSoco2011/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[14], col=colors_[14], pch=plotchar[14])
lines(budgetSteps,minCountRB_IPOP_CMA_ES/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[3], col=colors_[3], pch=plotchar[3])
lines(budgetSteps,minCountCmaes_pure/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[2], col=colors_[2], pch=plotchar[2])
lines(budgetSteps,minCountDESv2/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[1], col=colors_[1], pch=plotchar[1])
lines(budgetSteps,minCountCmaes_4N/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[7], col=colors_[7], pch=plotchar[7])
#legend(-0.08, 1.03, c('DES','CMA-ES', 'RB_IPOP_CMA_ES','jSO','LSHADE_SPACMA','EBOwithCMAR','IDEbestNsize','PPSO','MM_OED','DYYPO','TLBO-FL','MOS-CEC2012','MOS-CEC2013','MOS-SOCO2011'), text.font=2, cex=1.2, col=colors_[1:14],pch=plotchar[1:14], lty=linetype[1:14] )
#dev.off()
return(rplot)
}
combinedPlot <- function(){
#colors_ <- rainbow(16)
#colors_[3] <- colors_[16]
colors_ <<- c(rep("black",2),rep("white",12))
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
setEPS()
postscript( "combinedPlot.eps", width = 20, height = 18)
layout(mat = matrix(1:16,nrow = 4,ncol = 4,byrow = TRUE),heights = c(1,1,1,1,0.2))
par(oma=c(9, 6, 0, 6), mar=4*c(.1,.1,.1,.1), cex=1, las=1)
ecdfIEEE(10,1,3)
ecdfIEEE(30,1,3)
ecdfIEEE(50,1,3)
ecdfIEEE(100,1,3)
ecdfIEEE(10,4,10)
ecdfIEEE(30,4,10)
ecdfIEEE(50,4,10)
ecdfIEEE(100,4,10)
ecdfIEEE(10,11,20)
ecdfIEEE(30,11,20)
ecdfIEEE(50,11,20)
ecdfIEEE(100,11,20)
ecdfIEEE(10,21,30)
ecdfIEEE(30,21,30)
ecdfIEEE(50,21,30)
ecdfIEEE(100,21,30)
mtext("log10 of (f-evals / dimension)", 1, 0, outer=TRUE,padj=3,cex=2)
mtext("Proportion of function + target pairs", 2, 3, outer=TRUE, las=0,cex=2)
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), mar = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n")
legend("bottom", c('DES','CMA-ES'), text.font=2, cex=1.5, col=colors_[1:2],pch=plotchar[1:2], lty=linetype[1:2], ncol=2)
dev.off()
}
plotCECline <- function(){
colors_ <<- c(rep("black",2),rep("grey",4),"blue")
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
setEPS()
postscript( "plotCECline.eps", width = 20, height = 6)
layout(mat = matrix(1:4,nrow = 1,ncol = 4,byrow = TRUE),heights = c(1,0.2))
par(oma=c(7, 4, 0, 0), mar=4*c(.1,.1,.1,.1), cex=1, las=1)
ecdfIEEE(10,1,30)
ecdfIEEE(30,1,30)
ecdfIEEE(50,1,30)
ecdfIEEE(100,1,30)
mtext("log10 of (f-evals / dimension)", 1, 0, outer=TRUE,padj=3,cex=1.5)
mtext("Proportion of function + target pairs", 2, 3, outer=TRUE, las=0,cex=1.3)
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), mar = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n")
legend("bottom", c('DES','CMA-ES', 'RB_IPOP_CMA_ES ','jSO','LSHADE_SPACMA ','EBOwithCMAR','CMA-ES L=4N'), text.font=2, cex=1.3, col=colors_[1:7],pch=plotchar[1:7], lty=linetype[1:7], ncol=7)
dev.off()
}
plotAllSingle <- function(){
colors_ <<- c("red","orange","blue","green","brown","pink","black")
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
for(n in c(10,30,50,100)){
for(p in 1:30){
pdf( paste("Problem=",p,",N=",n,".pdf",sep=''), width = 10, height = 10)
ecdfIEEE(n,p,p)
legend(-0.08, 1.03, c('DES','CMA-ES', 'RB_IPOP_CMA_ES','jSO','LSHADE_SPACMA','EBOwithCMAR','CMA-ES L=4N'), text.font=2, cex=1.5, col=colors_[1:7],pch=plotchar[1:7], lty=linetype[1:7])
dev.off()
}
}
}
plotEcdfPresentation <- function(){
path <- "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/DESv2/DES + dMean custom1 (DESv2.5)/M/DES_1_10.txt"
resDES <- read.table(file = path,sep = ",")
budgetSteps <- c(0.01, 0.02, 0.03, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)
par(mfrow=c(1,1))
#plot(budgetSteps,resDES[,1],xlab="function evaluations / 10000*D",ylab="error value",log = "y", type="b", lwd=2,lty=1, col="red", pch=15,cex.lab=1.5,xaxt="n")
#axis(1, at=budgetSteps, labels=budgetSteps)
minCountDES <- c(0.08446456, 0.14264167, 0.18487395, 0.26330532, 0.38655462, 0.81017022, 0.91618186, 0.92243051, 0.92544710 ,0.92824822, 0.92889463, 0.92954105, 0.93040293, 0.93061840)
plot(budgetSteps*log10(10000),minCountDES, xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs", ylim=c(0, 1), type="b", lwd=2,lty=1, col="red", pch=15,cex.lab=1.5)
}
warbarbye/cecs-benchmark documentation built on March 10, 2020, 12:09 a.m.
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Defines functions ecdfIEEE combinedPlot plotCECline plotAllSingle plotEcdfPresentation
library(ggplot2)
ecdfIEEE<- function(n,f_from,f_to){
N <- n
F_from <- f_from
F_to <- f_to
print(paste("Dimension: ",n,sep=''))
#des_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMADE-BBComp5 HistSize=3sqrt(N) init(-80,80) FINALTEST/M/"
rb_ipop_cma_es_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/paper ID E-17343/RB-IPOP-CMA-ES/"
cmaes_pure = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES/M/"
cmaes_4N = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES L=4N/M/"
des_pathv2 = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/DESv2/DES - tol_v2/M/"
jsopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17315/jSO/"
lshadeSpacma_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17051/LSHADE_SPACMA/"
#cmaesNos_path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/CEC2017/CMAES noSigma/M/"
ebopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/EBOwithCMAR/data for email/"
#idepath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17322/IDEbestNsize/"
#ppsopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/paper ID E-17447/cec2017PPSO/"
#mmoedpath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17321/Multi-method based Orthogonal Experimental Design Algorithm for Solving CEC2017 Competition Problems results/"
#dyypopath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17543/DYYPO/"
#tlboflpath = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID 17544/TLBO-FL/"
#moscec2012path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_cec2012/"
#moscec2013path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_cec2013/"
#mossoco2011path = "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/IEEEecdf/Results for all papers/Paper ID E-17260/E-17260_results/res_soco2011/"
ecdfValues <- list()
budgetSteps <- c(0.01, 0.02, 0.03, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)*log10(10000)
#colors_ <- rainbow(16)
#colors_[6] <- rainbow(50)[50]
#colors_[3] <- colors_[16]
#colors_ <- c(rep("black",2),rep("grey",12))
#linetype <- c(c(1:6),c(1:6),c(1:6))
#plotchar <- c( seq(15,15+10,1),8,13,14,13)
ecdfMaxSucess <- 0
#resultsDES <- list()
resultsRB_IPOP_CMA_ES <- list()
resultsCmaes_pure <- list()
resultsCmaes_4n <- list()
resultsDESv2 <- list()
resultsjso <- list()
resultslshadeSpacma <- list()
#resultsCmaesNos <- list()
resultsEbo <- list()
resultsIDE <- list()
resultsPPSO <- list()
resultsMMOED <- list()
resultsDYYPO <- list()
resultsTLBOFL <- list()
resulsMOSCEC2012 <- list()
resulsMOSCEC2013 <- list()
resulsMOSSOCO2011 <- list()
for(p in 1:30){
#resultsDES[[p]] <- read.table(file = paste(des_path,"DES_",p,"_",N,".txt",sep=""),sep = ",")
resultsRB_IPOP_CMA_ES[[p]] <- read.table(file = paste(rb_ipop_cma_es_path,"RB-IPOP-CMA-ES_",p,"_",N,".txt",sep=""),sep = " ")
resultsCmaes_pure[[p]] <- read.table(file = paste(cmaes_pure,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
resultsDESv2[[p]] <- read.table(file = paste(des_pathv2,"DES_",p,"_",N,".txt",sep=""),sep = ",")
resultsjso[[p]] <- read.table(file = paste(jsopath,"jSO_",p,"_",N,".txt",sep=""))
resultslshadeSpacma[[p]] <- read.table(file = paste(lshadeSpacma_path,"LSHADE_SPACMA_",p,"_",N,".txt",sep=""))
#resultsCmaesNos[[p]] <- read.table(file = paste(cmaesNos_path,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
resultsEbo[[p]] <- read.table(file = paste(ebopath,"EBOwithCMAR_",p,"_",N,".dat",sep=""))
resultsCmaes_4n[[p]] <- read.table(file = paste(cmaes_4N,"CMAES_",p,"_",N,".txt",sep=""),sep = ",",header = TRUE)
#resultsIDE[[p]] <- read.table(file = paste(idepath,"IDEbestNsize_",N,"_",p,".txt",sep=""))
#resultsPPSO[[p]] <- read.table(file = paste(ppsopath,"PPSO_",p,"_",N,".txt",sep=""))
#resultsMMOED[[p]] <- read.table(file = paste(mmoedpath,"MM_OED_",p,"_",N,".txt",sep=""))
#resultsDYYPO[[p]] <- read.table(file = paste(dyypopath,"DYYPO_",p,"_",N,".txt",sep=""))
#resultsTLBOFL[[p]] <- read.table(file = paste(tlboflpath,"TLBO-FL_",p,"_",N,".txt",sep=""))
#resulsMOSCEC2012[[p]] <- read.table(file = paste(moscec2012path,"MOS-CEC2012_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
#resulsMOSCEC2013[[p]] <- read.table(file = paste(moscec2013path,"MOS-CEC2013_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
#resulsMOSSOCO2011[[p]] <- read.table(file = paste(mossoco2011path,"MOS-SOCO2011_",p,"_",N,".csv",sep=""),sep=",",header = TRUE, colClasses=c("NULL",rep(NA,51)))
ecdfValues[[p]] <- rev(c(1 %o% (10)^(0.2*((log10(max(min(
#min(resultsDES[[p]][14,]),
min(resultsRB_IPOP_CMA_ES[[p]][14,]),
min(resultsCmaes_pure[[p]][14,]),
min(resultsDESv2[[p]][14,]),
min(resultsjso[[p]][14,]),
min(resultslshadeSpacma[[p]][14,]),
#min(resultsCmaesNos[[p]][14,]),
min(resultsEbo[[p]][14,]),
min(resultsCmaes_4n[[p]][14,])
#min(resultsIDE[[p]][14,]),
#min(resultsPPSO[[p]][14,]),
#min(resultsMMOED[[p]][14,]),
#min(resultsDYYPO[[p]][14,]),
#min(resultsTLBOFL[[p]][14,]),
#min(resulsMOSCEC2012[[p]][14,]),
#min(resulsMOSCEC2013[[p]][14,]),
#min(resulsMOSSOCO2011[[p]][14,])
),10^-8) )/0.2):(log10(max(
#max(resultsDES[[p]][1,]),
max(resultsRB_IPOP_CMA_ES[[p]][1,]),
max(resultsCmaes_pure[[p]][1,]),
max(resultsDESv2[[p]][1,]),
max(resultsjso[[p]][1,]),
max(resultslshadeSpacma[[p]][1,]),
#max(resultsCmaesNos[[p]][1,]),
max(resultsEbo[[p]][1,]),
max(resultsCmaes_4n[[p]][1,])
#max(resultsIDE[[p]][1,]),
#max(resultsPPSO[[p]][1,]),
#max(resultsMMOED[[p]][1,]),
#max(resultsDYYPO[[p]][1,]),
#max(resultsTLBOFL[[p]][1,]),
#max(resulsMOSCEC2012[[p]][1,]),
#max(resulsMOSCEC2013[[p]][1,]),
#max(resulsMOSSOCO2011[[p]][1,])
) )/0.2) ))))
}
#minCountDES <- rep(0,length(budgetSteps))
minCountRB_IPOP_CMA_ES <- rep(0,length(budgetSteps))
minCountCmaes_pure <- rep(0,length(budgetSteps))
minCountDESv2 <- rep(0,length(budgetSteps))
minCountjso <- rep(0,length(budgetSteps))
minCountshadeSpacma <- rep(0,length(budgetSteps))
#minCountCmaes_nos <- rep(0,length(budgetSteps))
minCountEbo <- rep(0,length(budgetSteps))
minCountCmaes_4N <- rep(0,length(budgetSteps))
minCountIde <- rep(0,length(budgetSteps))
minCountPpso <- rep(0,length(budgetSteps))
minCountMmoed <- rep(0,length(budgetSteps))
minCountDyypo <- rep(0,length(budgetSteps))
minCountTlbofl <- rep(0,length(budgetSteps))
minCountMosCec2012 <- rep(0,length(budgetSteps))
minCountMosCec2013 <- rep(0,length(budgetSteps))
minCountMosSoco2011 <- rep(0,length(budgetSteps))
for(p in F_from:F_to){
print(paste("Calculating for function: ",p))
for(b in 1:length(budgetSteps)){
for(e in 1:length(ecdfValues[[p]])){
#minCountDES[b] <- minCountDES[b] + sum(resultsDES[[p]][b,]<ecdfValues[[p]][e])
minCountRB_IPOP_CMA_ES[b] <- minCountRB_IPOP_CMA_ES[b] + sum(resultsRB_IPOP_CMA_ES[[p]][b,]<ecdfValues[[p]][e])
minCountCmaes_pure[b] <- minCountCmaes_pure[b] + sum(resultsCmaes_pure[[p]][b,]<ecdfValues[[p]][e])
minCountDESv2[b] <- minCountDESv2[b] + sum(resultsDESv2[[p]][b,]<ecdfValues[[p]][e])
minCountjso[b] <- minCountjso[b] + sum(resultsjso[[p]][b,]<ecdfValues[[p]][e])
minCountshadeSpacma[b] <- minCountshadeSpacma[b] + sum(resultslshadeSpacma[[p]][b,]<ecdfValues[[p]][e])
#minCountCmaes_nos[b] <- minCountCmaes_nos[b] + sum(resultsCmaesNos[[p]][b,]<ecdfValues[[p]][e])
minCountEbo[b] <- minCountEbo[b] + sum(resultsEbo[[p]][b,]<ecdfValues[[p]][e])
minCountCmaes_4N[b] <- minCountCmaes_4N[b] + sum(resultsCmaes_4n[[p]][b,]<ecdfValues[[p]][e])
#minCountIde[b] <- minCountIde[b] + sum(resultsIDE[[p]][b,]<ecdfValues[[p]][e])
#minCountPpso[b] <- minCountPpso[b] + sum(resultsPPSO[[p]][b,]<ecdfValues[[p]][e])
#minCountMmoed[b] <- minCountMmoed[b] + sum(resultsMMOED[[p]][b,]<ecdfValues[[p]][e])
#minCountDyypo[b] <- minCountDyypo[b] + sum(resultsDYYPO[[p]][b,]<ecdfValues[[p]][e])
#minCountTlbofl[b] <- minCountTlbofl[b] + sum(resultsTLBOFL[[p]][b,]<ecdfValues[[p]][e])
#minCountMosCec2012[b] <- minCountMosCec2012[b] + sum(resulsMOSCEC2012[[p]][b,]<ecdfValues[[p]][e])
#minCountMosCec2013[b] <- minCountMosCec2013[b] + sum(resulsMOSCEC2013[[p]][b,]<ecdfValues[[p]][e])
#minCountMosSoco2011[b] <- minCountMosSoco2011[b] + sum(resulsMOSSOCO2011[[p]][b,]<ecdfValues[[p]][e])
}
}
ecdfMaxSucess <- ecdfMaxSucess + length(ecdfValues[[p]])*51
}
# All single plot
isYaxt <- "s"
isXaxt <- "s"
# Line plot
#isXaxt <- "s"
#isYaxt <- if(N==10) "s" else "n"
# Combined plot
#isYaxt <- if(N==10) "s" else "n"
#isXaxt <- if(F_from==21) "s" else "n"
#setEPS()
# postscript( paste("Problems",F_from,"-",F_to,",N=",N,".eps",sep=""), width = 15, height = 15)
#xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs",
rplot <- plot(budgetSteps,minCountjso/(ecdfMaxSucess),xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs",ylim=c(0, 1),type="b", lwd=2,lty=linetype[4], col=colors_[4], pch=plotchar[4], xaxt=isXaxt, yaxt=isYaxt, cex.axis=1.5)
lines(budgetSteps,minCountshadeSpacma/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[5], col=colors_[5], pch=plotchar[5])
lines(budgetSteps,minCountEbo/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[6], col=colors_[6], pch=plotchar[6])
#lines(budgetSteps,minCountIde/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[7], col=colors_[7], pch=plotchar[7])
#lines(budgetSteps,minCountPpso/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[8], col=colors_[8], pch=plotchar[8])
#lines(budgetSteps,minCountMmoed/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[9], col=colors_[9], pch=plotchar[9])
#lines(budgetSteps,minCountDyypo/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[10], col=colors_[10], pch=plotchar[10])
#lines(budgetSteps,minCountTlbofl/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[11], col=colors_[11], pch=plotchar[11])
#lines(budgetSteps,minCountMosCec2012/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[12], col=colors_[12], pch=plotchar[12])
#lines(budgetSteps,minCountMosCec2013/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[13], col=colors_[13], pch=plotchar[13])
#lines(budgetSteps,minCountMosSoco2011/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[14], col=colors_[14], pch=plotchar[14])
lines(budgetSteps,minCountRB_IPOP_CMA_ES/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[3], col=colors_[3], pch=plotchar[3])
lines(budgetSteps,minCountCmaes_pure/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[2], col=colors_[2], pch=plotchar[2])
lines(budgetSteps,minCountDESv2/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[1], col=colors_[1], pch=plotchar[1])
lines(budgetSteps,minCountCmaes_4N/(ecdfMaxSucess),type="b", lwd=2,lty=linetype[7], col=colors_[7], pch=plotchar[7])
#legend(-0.08, 1.03, c('DES','CMA-ES', 'RB_IPOP_CMA_ES','jSO','LSHADE_SPACMA','EBOwithCMAR','IDEbestNsize','PPSO','MM_OED','DYYPO','TLBO-FL','MOS-CEC2012','MOS-CEC2013','MOS-SOCO2011'), text.font=2, cex=1.2, col=colors_[1:14],pch=plotchar[1:14], lty=linetype[1:14] )
#dev.off()
return(rplot)
}
combinedPlot <- function(){
#colors_ <- rainbow(16)
#colors_[3] <- colors_[16]
colors_ <<- c(rep("black",2),rep("white",12))
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
setEPS()
postscript( "combinedPlot.eps", width = 20, height = 18)
layout(mat = matrix(1:16,nrow = 4,ncol = 4,byrow = TRUE),heights = c(1,1,1,1,0.2))
par(oma=c(9, 6, 0, 6), mar=4*c(.1,.1,.1,.1), cex=1, las=1)
ecdfIEEE(10,1,3)
ecdfIEEE(30,1,3)
ecdfIEEE(50,1,3)
ecdfIEEE(100,1,3)
ecdfIEEE(10,4,10)
ecdfIEEE(30,4,10)
ecdfIEEE(50,4,10)
ecdfIEEE(100,4,10)
ecdfIEEE(10,11,20)
ecdfIEEE(30,11,20)
ecdfIEEE(50,11,20)
ecdfIEEE(100,11,20)
ecdfIEEE(10,21,30)
ecdfIEEE(30,21,30)
ecdfIEEE(50,21,30)
ecdfIEEE(100,21,30)
mtext("log10 of (f-evals / dimension)", 1, 0, outer=TRUE,padj=3,cex=2)
mtext("Proportion of function + target pairs", 2, 3, outer=TRUE, las=0,cex=2)
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), mar = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n")
legend("bottom", c('DES','CMA-ES'), text.font=2, cex=1.5, col=colors_[1:2],pch=plotchar[1:2], lty=linetype[1:2], ncol=2)
dev.off()
}
plotCECline <- function(){
colors_ <<- c(rep("black",2),rep("grey",4),"blue")
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
setEPS()
postscript( "plotCECline.eps", width = 20, height = 6)
layout(mat = matrix(1:4,nrow = 1,ncol = 4,byrow = TRUE),heights = c(1,0.2))
par(oma=c(7, 4, 0, 0), mar=4*c(.1,.1,.1,.1), cex=1, las=1)
ecdfIEEE(10,1,30)
ecdfIEEE(30,1,30)
ecdfIEEE(50,1,30)
ecdfIEEE(100,1,30)
mtext("log10 of (f-evals / dimension)", 1, 0, outer=TRUE,padj=3,cex=1.5)
mtext("Proportion of function + target pairs", 2, 3, outer=TRUE, las=0,cex=1.3)
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), mar = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n")
legend("bottom", c('DES','CMA-ES', 'RB_IPOP_CMA_ES ','jSO','LSHADE_SPACMA ','EBOwithCMAR','CMA-ES L=4N'), text.font=2, cex=1.3, col=colors_[1:7],pch=plotchar[1:7], lty=linetype[1:7], ncol=7)
dev.off()
}
plotAllSingle <- function(){
colors_ <<- c("red","orange","blue","green","brown","pink","black")
linetype <<- c(c(1:6),c(1:6),c(1:6))
plotchar <<- c( 15,1,seq(16,15+8,1),8,13,14,13)
for(n in c(10,30,50,100)){
for(p in 1:30){
pdf( paste("Problem=",p,",N=",n,".pdf",sep=''), width = 10, height = 10)
ecdfIEEE(n,p,p)
legend(-0.08, 1.03, c('DES','CMA-ES', 'RB_IPOP_CMA_ES','jSO','LSHADE_SPACMA','EBOwithCMAR','CMA-ES L=4N'), text.font=2, cex=1.5, col=colors_[1:7],pch=plotchar[1:7], lty=linetype[1:7])
dev.off()
}
}
}
plotEcdfPresentation <- function(){
path <- "C:/Users/JS/Desktop/Doktorat/EvolutionAlgorithms/DESv2/DES + dMean custom1 (DESv2.5)/M/DES_1_10.txt"
resDES <- read.table(file = path,sep = ",")
budgetSteps <- c(0.01, 0.02, 0.03, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0)
par(mfrow=c(1,1))
#plot(budgetSteps,resDES[,1],xlab="function evaluations / 10000*D",ylab="error value",log = "y", type="b", lwd=2,lty=1, col="red", pch=15,cex.lab=1.5,xaxt="n")
#axis(1, at=budgetSteps, labels=budgetSteps)
minCountDES <- c(0.08446456, 0.14264167, 0.18487395, 0.26330532, 0.38655462, 0.81017022, 0.91618186, 0.92243051, 0.92544710 ,0.92824822, 0.92889463, 0.92954105, 0.93040293, 0.93061840)
plot(budgetSteps*log10(10000),minCountDES, xlab="log10 of (f-evals / dimension)",ylab="Proportion of function + target pairs", ylim=c(0, 1), type="b", lwd=2,lty=1, col="red", pch=15,cex.lab=1.5)
}
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