Include individual graphs.

[loba-papers.git] / supercomp11 / data / script.r

diff --git a/supercomp11/data/script.r b/supercomp11/data/script.r
index ffac78310bf7bb3d7b7d7ccafd5333d94e281603..52af905351a19e73c5c50cc17001ef0c0e68f0b5 100644 (file)
--- a/supercomp11/data/script.r
+++ b/supercomp11/data/script.r
@@ -1,13 +1,208 @@
-# load dataset (variable is "ds")
+## 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")
 
 load("data.rda")
 

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

 
 

-xx <- subset(ds.base, Ratio == "1:1" & Topo == "line" & Distrib == 1)
-plot(xx$Size, xx$Conv_max, xlab="Size", ylab="Time")
+  ## rename rows
+  rownames(dset.wide) <- dset.wide$Algo
+  #colnames(dset.wide) <- sub("^[^.]*\\.", "", colnames(dset.wide))
+
+  ## remove first column (aka "Algo")
+  dset.mat <- as.matrix(dset.wide[-1])
+
+  dset.plot <- dset.mat[, c(FALSE,FALSE,TRUE)]
+  barplot(dset.plot, beside=TRUE,
+          names.arg=sub("^[^.]*\\.", "", colnames(dset.plot)),
+          col=rainbow(nrow(dset.mat), s=.5))
+
+  dset.plot <- dset.mat[, c(FALSE,TRUE,FALSE)]
+  barplot(dset.plot, beside=TRUE,
+          axes=FALSE, axisnames=FALSE, add=TRUE,
+          legend.text=TRUE,
+          args.legend=list(x="topleft", inset=c(.02,0), title="Algorithms"),
+          col=rainbow(nrow(dset.mat)))
+
+  dset.plot <- dset.mat[, c(TRUE,FALSE,FALSE)]
+  barplot(dset.plot, beside=TRUE,
+          axes=FALSE, axisnames=FALSE, add=TRUE,
+          col=rainbow(nrow(dset.mat), v=.5))
+
+  ## finally, set titles
+  t <- paste0(dset$Mode[1], dset$Distrib[1], " / ",
+              dset$Ratio[1], " / ",
+              dset$Platform[1], " / ", dset$Topo[1])
+  title(xlab="Platform size",
+        ylab="Simulated time (s)",
+        main=t)

 
 

-for(pl in c("cluster", "grid")) {
-   yy <- subset(xx, Platform == pl)
-   points(yy$Size, yy$Conv_max, xlab="Size", ylab="Time")

 }
 }

+
+msg <- function(text,
+                wait = TRUE) {
+  if (wait)
+    readline("Press <Enter> to continue\n")
+  message(text)
+}
+
+if (FALSE) {
+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")
+}
+
+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))
+          pdf(file=sprintf("graphs/%s%s-%s-%s-%s.pdf", m, d, r, p, t))
+          draw2(#subset(ds, grepl("[lt]_plain", Algo)),
+                draw_mode=m, draw_distrib=d, draw_ratio=r,
+                draw_topo=t, draw_platform=p)
+          dev.off()
+        }
+      }
+    }
+  }
+}
+
+## restore default options
+options(scipen=osp)