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

## 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)

### TODO
### - add some spacing between each size
### - fill in empty rows (e.g. with large size)
### - add a label telling the size

  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("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)

}

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)))

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

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