Finalize graph generation.

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

diff --git a/supercomp11/data/script.r b/supercomp11/data/script.r
index 3440b86ebe9f81b77a8a942f9ec8fab041f28b8b..52af905351a19e73c5c50cc17001ef0c0e68f0b5 100644 (file)
--- a/supercomp11/data/script.r
+++ b/supercomp11/data/script.r
@@ -1,5 +1,9 @@
 ## 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")
 
@@ -39,11 +43,6 @@ draw <- function(dset = ds,
   ## 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))
 
@@ -63,7 +62,7 @@ draw <- function(dset = ds,
 
   ## draw the time axis on the left
   axis(2, labels=TRUE)
-  mtext("Simulated Time (s)", side=2, line=2.5)
+  mtext("Simulated time (s)", side=2, line=2.5)
 
   title(xlab="Algorithms")
 
@@ -98,45 +97,64 @@ draw <- function(dset = ds,
   return(dset)
 }
 
-draw2 <- function(dset) {
-  ## Extract useful data
-  x.1 <- data.frame(Algo=dset$Algo, Size=dset$Size,
-                    Idle_avg=dset$Idle_avg,
-                    Conv_avg=dset$Conv_avg,
-                    Conv_max=dset$Conv_max)
+draw2 <- function(dset = ds,
+                 draw_mode = "R",
+                 draw_distrib = 1,
+                 draw_ratio = "1:1",
+                 draw_platform = "cluster",
+                 draw_topo = "hcube") {
+
+  ## extract desired data
+  dset <- subset(dset,
+                 Mode == draw_mode & Distrib == draw_distrib &
+                 Ratio == draw_ratio &
+                 Platform == draw_platform & Topo == draw_topo)
+
+  ## reorder lines (first "plain", then "bookkeeping")
+  dset <- rbind(subset(dset, grepl("plain", Algo)),
+                subset(dset, grepl("bookkeeping", Algo)))
+  dset <- dset[order(dset$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
-  x.2 <- reshape(x.1, direction="wide", idvar="Algo", timevar="Size")
+  ## reshape data -> wide
+  dset.wide <- reshape(dset.long, direction="wide",
+                       idvar="Algo", timevar="Size")
 
-  ## Rename rows
-  rownames(x.2) <- x.2$Algo
-  #colnames(x.2) <- sub("^[^.]*\\.", "", colnames(x.2))
+  ## rename rows
+  rownames(dset.wide) <- dset.wide$Algo
+  #colnames(dset.wide) <- sub("^[^.]*\\.", "", colnames(dset.wide))
 
-  ## Remove first column ("Algo")
-  x.3 <- as.matrix(x.2[-1])
+  ## remove first column (aka "Algo")
+  dset.mat <- as.matrix(dset.wide[-1])
 
-  x.4 <- x.3[, c(FALSE,FALSE,TRUE)]
-  barplot(x.4, beside=TRUE,
-          names.arg=sub("^[^.]*\\.", "", colnames(x.4)),
-          col=rainbow(nrow(x.3), s=.5))
+  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))
 
-  x.4 <- x.3[, c(FALSE,TRUE,FALSE)]
-  barplot(x.4, beside=TRUE,
+  dset.plot <- dset.mat[, c(FALSE,TRUE,FALSE)]
+  barplot(dset.plot, beside=TRUE,
           axes=FALSE, axisnames=FALSE, add=TRUE,
           legend.text=TRUE,
-          col=rainbow(nrow(x.3)))
+          args.legend=list(x="topleft", inset=c(.02,0), title="Algorithms"),
+          col=rainbow(nrow(dset.mat)))
 
-  x.4 <- x.3[, c(TRUE,FALSE,FALSE)]
-  barplot(x.4, beside=TRUE,
+  dset.plot <- dset.mat[, c(TRUE,FALSE,FALSE)]
+  barplot(dset.plot, beside=TRUE,
           axes=FALSE, axisnames=FALSE, add=TRUE,
-          col=rainbow(nrow(x.3), v=.5))
+          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)",
+  title(xlab="Platform size",
+        ylab="Simulated time (s)",
         main=t)
 
 }
@@ -148,22 +166,43 @@ msg <- function(text,
   message(text)
 }
 
+if (FALSE) {
 msg("First test, with algorithms \"plain\"...", wait = FALSE);
-xx <- draw(subset(ds, grepl("[lt]_plain", Algo)),
-           draw_distrib="N")
+draw(subset(ds, grepl("[lt]_plain", Algo)), draw_distrib="N")
 
 msg("... with draw2()...")
-draw2(xx)
+draw2(subset(ds, grepl("[lt]_plain", Algo)), draw_distrib="N")
 
 msg("Second test, with algorithms \"bookkeeping\"...");
-xx <- draw(subset(ds, grepl("[lt]_bookkeeping", Algo)),
-           draw_distrib="N")
+draw(subset(ds, grepl("[lt]_bookkeeping", Algo)), draw_distrib="N")
 
 msg("... with draw2()...")
-draw2(xx)
+draw2(subset(ds, grepl("[lt]_bookkeeping", Algo)), draw_distrib="N")
 
 msg("Third test, with all algorithms...");
-xx <- draw(draw_distrib="N")
+draw(draw_distrib="N")
 
 msg("... with draw2()...")
-draw2(xx)
+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)