## Usage: launch R, and then: source("script.r")

## save, and chane default options
osp <- options("scipen")
options(scipen=3)

## load dataset (variable is "ds")
load("data.rda")

## extract data for plain algorithms, in real mode
#ds.base <- subset(ds, Mode == "R" & grepl("[lt]_plain", Algo))

## extract data for one experiment
#xx <- subset(ds,
#             Mode == "R" & Distrib == 1 & Ratio == "1:1" &
#             Platform == "cluster" & Size == 16 & Topo == "line")



draw <- function(dset = ds,
                 draw_mode = "R",
                 draw_distrib = 1,
                 draw_ratio = "1:1",
                 draw_platform = "cluster",
                 draw_topo = "hcube") {

  ## extract desired data
  dset <- subset(dset,
                 Mode == draw_mode & Distrib == draw_distrib &
                 Ratio == draw_ratio &
                 Platform == draw_platform & Topo == draw_topo)

  ## reorder lines (first "plain", then "bookkeeping")
  dset <- rbind(subset(dset, grepl("plain", Algo)),
                subset(dset, grepl("bookkeeping", Algo)))
  dset <- dset[order(dset$Size), ]

  ## finally, add an "Index" attribute(, for further processing
  dset <- cbind(dset, Index=seq(1, length(dset$Size))) # FIXME

  #print(dset)

  ## save the graphical parameters
  p <- par(no.readonly=TRUE)

  par(mar=c(13, 4, 4, 4) + 0.1,         # change margins
      mgp=c(11, 1, 0))

  par(las=3)                           # always draw labels vertically

  ## compute the time range: 0..max+20%
  time_range <- c(0, range(dset$Conv_max)[2] * 1.2)

  ## first draw the bars
  barplot(dset$Conv_max, axes=FALSE, col="red",
          names=dset$Algo,
          ylim=time_range)
  barplot(dset$Conv_avg, axes=FALSE, col="green",
          add=TRUE)
  barplot(dset$Idle_avg, axes=FALSE, col="blue",
          add=TRUE)

  ## draw the time axis on the left
  axis(2, labels=TRUE)
  mtext("Simulated time (s)", side=2, line=2.5)

  title(xlab="Algorithms")

  ## compute the data range
  x_data_range <- c(0.6, length(dset$Algo) + 0.4)
  data_range <- c(0, range(dset$Data_amnt)[2] * 1.04)

  ## draw the data amnt line graphs
  for (alg in unique(dset$Algo)) {
    print(alg);
    dset.da <- subset(dset, Algo == alg)
    ## start a new graph, but drawn on the same device
    par(new=TRUE)
    plot(dset.da$Index, dset.da$Data_amnt, axes=FALSE, xlab="", type="b",
         xlim=x_data_range,
         yaxs="i", ylim=data_range)
  }

  ## draw the data amnt axis on the right
  axis(4, labels=TRUE)
  mtext("Data amount (relative)", side=4, line=2.5)

  ## finally, set title
  t <- paste0(dset$Mode[1], dset$Distrib[1], " / ",
              dset$Ratio[1], " / ",
              dset$Platform[1], " / ", dset$Topo[1])
  title(main=t)

  ## restore the graphical parameters
  par(p)

  return(dset)
}

draw2 <- function(dset = ds,
                 draw_mode = "R",
                 draw_distrib = 1,
                 draw_ratio = "1:1",
                 draw_platform = "cluster",
                 draw_topo = "hcube") {

  ## extract desired data
  dset <- subset(dset,
                 Mode == draw_mode & Distrib == draw_distrib &
                 Ratio == draw_ratio &
                 Platform == draw_platform & Topo == draw_topo)

  ## reorder lines (first "plain", then "bookkeeping")
  dset <- rbind(subset(dset, grepl("plain", Algo)),
                subset(dset, grepl("bookkeeping", Algo)))
  dset <- dset[order(dset$Size), ]

  ## keep only useful data
  dset.long <- data.frame(Algo=dset$Algo, Size=dset$Size,
                          Idle_avg=dset$Idle_avg,
                          Conv_avg=dset$Conv_avg,
                          Conv_max=dset$Conv_max)

  ## reshape data -> wide
  dset.wide <- reshape(dset.long, direction="wide",
                       idvar="Algo", timevar="Size")

  ## rename rows
  names <- dset.wide$Algo
  names <- sub("makhoul_plain",             "a: makhoul,plain", names)
  names <- sub("besteffort_plain",          "b: best effort,plain", names)
  names <- sub("besteffort-k2_plain",       "c: best effort,k=2,plain", names)
  names <- sub("besteffort-k4_plain",       "d: best effort,k=4,plain", names)
  names <- sub("makhoul_bookkeeping",       "e: makhoul,virtual", names)
  names <- sub("besteffort_bookkeeping",    "f: best effort,virtual", names)
  names <- sub("besteffort-k2_bookkeeping", "g: best effort,k=2,virtual", names)
  names <- sub("besteffort-k4_bookkeeping", "h: best effort,k=4,virtual", names)
  rownames(dset.wide) <- names
  #colnames(dset.wide) <- sub("^[^.]*\\.", "", colnames(dset.wide))

  ## remove first column (aka "Algo")
  dset.mat <- as.matrix(dset.wide[-1])
  nc <- nrow(dset.mat)

  dset.plot <- dset.mat[, c(FALSE,FALSE,TRUE)]
  barplot(dset.plot, beside=TRUE,
          axisnames=FALSE,
#          names.arg=sub("^[^.]*\\.", "", colnames(dset.plot)),
          col=gray.colors(nc)
#          col=rainbow(nc, s=.5)
          )

  dset.plot <- dset.mat[, c(FALSE,TRUE,FALSE)]
  barplot(dset.plot, beside=TRUE,
          axes=FALSE, axisnames=FALSE, add=TRUE,
          legend.text=TRUE,
          args.legend=list(x="topleft", inset=c(.02,0), x.intersp=0.5, title="Algorithms"),
          col=gray.colors(nc)
#          col=rainbow(nc)
          )

  dset.plot <- dset.mat[, c(TRUE,FALSE,FALSE)]
  barplot(dset.plot, beside=TRUE,
          axes=FALSE, axisnames=FALSE, add=TRUE,
          col="white"
#          col=gray.colors(nc)
#          col=rainbow(nc, v=.5)
          )

  ## finally, set titles
  c <- ncol(dset.plot) - 1
  for (l in 0:7) {
    t <- intToUtf8(utf8ToInt("a") + l)
    for (a in 1.5 + l + 9 * 0:c)
      mtext(t, side=1, at=a)
  }
  a=5
  for (s in sub("^[^.]*\\.", "", colnames(dset.plot))) {
    mtext(s, side=1, line=1.5, at=a)
    a <- a + 9
  }
  t <- paste0(dset$Mode[1], dset$Distrib[1], " / ",
              dset$Ratio[1], " / ",
              dset$Platform[1], " / ", dset$Topo[1])
  t <- sub("hcube", "hypercube", t)
  title(xlab="Platform size",
        ylab="Simulated time (s)",
        main=t)

}

if (FALSE) {

  if (TRUE) {
    draw2(draw_distrib="1")
    draw2(draw_distrib="N")
  } else {
    msg <- function(text, wait = TRUE) {
      if (wait)
        readline("Press <Enter> to continue\n")
      message(text)
    }

    msg("First test, with algorithms \"plain\"...", wait = FALSE);
    draw(subset(ds, grepl("[lt]_plain", Algo)), draw_distrib="N")

    msg("... with draw2()...")
    draw2(subset(ds, grepl("[lt]_plain", Algo)), draw_distrib="N")

    msg("Second test, with algorithms \"bookkeeping\"...");
    draw(subset(ds, grepl("[lt]_bookkeeping", Algo)), draw_distrib="N")

    msg("... with draw2()...")
    draw2(subset(ds, grepl("[lt]_bookkeeping", Algo)), draw_distrib="N")

    msg("Third test, with all algorithms...");
    draw(draw_distrib="N")

    msg("... with draw2()...")
    draw2(draw_distrib="N")
  }

} else {

  pdf.options(colormodel="grey")
  system("mkdir -pv graphs")
  for (m in c("R", "I")) {
    for (d in c("1", "N")) {
      for (r in c("10:1", "1:1", "1:10")) {
        for (t in c("line", "torus", "hcube")) {
          for (p in c("grid", "cluster")) {
            message(sprintf(">>> Drawing: %s%s / %s / %s / %s", m, d, r, p, t))
          filename <- sprintf("graphs/%s%s-%s-%s-%s.pdf", m, d, r, p, t)
            pdf(file=filename)
            draw2(#subset(ds, grepl("[lt]_plain", Algo)),
                  draw_mode=m, draw_distrib=d, draw_ratio=r,
                  draw_topo=t, draw_platform=p)
            dev.off()
            embedFonts(file=filename, options="-dPDFSETTINGS=/prepress")
          }
        }
      }
    }
  }

  ## restore default options
  options(scipen=osp)
}