plot_iterations_as_plotly.oms

// this variable will transmit the path where the CSV files to graph will be found 
val directoryWithResults = Val[File]

// variables used to parameter the graphing function 
val filesHaveHeaders = Val[Int]
val countInputs = Val[Int]

// this variable will contain the file with the graphical rendering of the last PAreto front
val plotlyPage = Val[File]

val taskPlotAsVideo = RTask("""
    library(ggplot2)
    library(plotly)
    library(htmlwidgets)

    colnames <- if (countInputs == 2) c("iteration", "x", "y", "f1", "f2") else c("iteration", "x", "f1", "f2")
    coltypes <- if (countInputs == 2) c("integer", "numeric", "numeric", "numeric", "numeric") else c("integer", "numeric", "numeric", "numeric") 
    names(coltypes) <- colnames
    
    directoryWithResultsName <- "mydirectory"

    pop <- NULL
    i <- 1
    while (TRUE) {
    	# TODO check creation time of the file
    	filename <- paste(directoryWithResultsName,"/population",i,".csv", sep="");
    	if (!file.exists(filename)) {
    		break
    	}
    	#print(filename)
    	popraw <- read.csv(header = FALSE, col.names=colnames, colClasses=coltypes, file=filename)
    	#print(head(popraw))
    
    	pop <- if (is.null(pop)) popraw else rbind(pop, popraw)
    		
    	i <- i + 1
    }
    
    # the ggplot 
    pop$index <- 1:nrow(pop) # add an index to avoid animation of points which are not at all similar 
    p <- ggplot(pop, aes(x=f1,y=f2,l1=x)
        ) + geom_point(
            alpha=0.7, colour = "#51A0D5", aes(frame=iteration,ids=index)
        ) + labs(
            x = "f1", 
            y = "f2",
            title = "Evolution of the Pareto front with NSGA2"
        ) + theme_classic()

    # render as plotly
    dir.create("/tmp/plotly")
    fig <- ggplotly(p)
    saveWidget(fig, selfcontained=F, file = "/tmp/plotly/evolution.html")
    lf <- list.files("/tmp/plotly/", recursive=T, include.dirs=F)
    print(lf)
    
    # zip resulting files 
    library(zip)
    setwd("/tmp/plotly/")
    zip("/tmp/evolution.zip", lf)
    
    print("done")
    
    """,
        install = Seq(
       // update the list of available packages
        "fakeroot apt-get update ",
        // required; attempts to update dbus to a newer version would require permissions we do not have
        "DEBIAN_FRONTEND=noninteractive fakeroot apt-mark hold dbus", 
        """echo "dbus hold" | fakeroot dpkg --set-selections""",
        // install the libs required for the compilation of R packages
        "DEBIAN_FRONTEND=noninteractive fakeroot apt-get install -y libssl-dev libcurl4-openssl-dev libudunits2-dev",
        // install required R packages in their binary version (quicker, much stable!)
        "DEBIAN_FRONTEND=noninteractive fakeroot apt-get install -y r-cran-ggplot2 r-cran-gganimate r-cran-ggally r-cran-plotly r-cran-zip",
        // install external tools in the VM for rendering
        "DEBIAN_FRONTEND=noninteractive fakeroot apt-get install -y ffmpeg",
        ), //  
    libraries = Seq() // were installed with the binary version earlier
) set (
    inputFiles += (directoryWithResults, "mydirectory"),
    outputFiles += ("/tmp/evolution.zip", plotlyPage),
    inputs += filesHaveHeaders.mapped,
    inputs += countInputs.mapped,
    filesHaveHeaders := 1,
    countInputs := 2
)

// import from the other file an example of optimization 
import _file_.example_of_optimization._

    // run the optimization 
(    evolutionSchafferN2 on envMultiThread hook (workDirectory/relativePath, keepAll=false)
) -- (
    // then run the plotting function 
taskPlotAsVideo set (
    // ... which will read all the results from this file 
    directoryWithResults := workDirectory / relativePath, 
    // ... analyze them knowing there is only one input in the files
    countInputs := 1
    ) hook CopyFileHook(plotlyPage, workDirectory/"evolutionPlotly.zip" ) 
    )