X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/loba-papers.git/blobdiff_plain/6b08fc897e84212c0dcabab251bb10dc0b248a17..3c2f33b63a5a1a5dd563955b54c361efaa0d2690:/supercomp11/data/script.r

diff --git a/supercomp11/data/script.r b/supercomp11/data/script.r
index f15d382..ec331ea 100644
--- a/supercomp11/data/script.r
+++ b/supercomp11/data/script.r
@@ -1,92 +1,208 @@
-# Usage: launch R, and then: source("script.r")
+## Usage: launch R, and then: source("script.r")
 
-# load dataset (variable is "ds")
+## 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 plain algorithms, in real mode
+#ds.base <- subset(ds, Mode == "R" & grepl("[lt]_plain", Algo))
 
-# extract data for one experiment
+## extract data for one experiment
 #xx <- subset(ds,
 #             Mode == "R" & Distrib == 1 & Ratio == "1:1" &
 #             Platform == "cluster" & Size == 16 & Topo == "line")
 
-xx <- subset(ds,
-             Mode == "R" & Distrib == "N" & Ratio == "1:1" &
-             Platform == "cluster" & Topo == "hcube")
 
-# only keep plain algorithms with default value for k...
-xx <- subset(xx, grepl("[lt]_plain", Algo))
 
-# reorder lines (first "plain", then "bookkeeping")
-xx <- rbind(subset(xx, grepl("plain", Algo)),
-            subset(xx, grepl("bookkeeping", Algo)))
-xx <- xx[order(xx$Size), ]
+draw <- function(dset = ds,
+                 draw_mode = "R",
+                 draw_distrib = 1,
+                 draw_ratio = "1:1",
+                 draw_platform = "cluster",
+                 draw_topo = "hcube") {
+
+  ## extract desired data
+  dset <- subset(dset,
+                 Mode == draw_mode & Distrib == draw_distrib &
+                 Ratio == draw_ratio &
+                 Platform == draw_platform & Topo == draw_topo)
+
+  ## reorder lines (first "plain", then "bookkeeping")
+  dset <- rbind(subset(dset, grepl("plain", Algo)),
+                subset(dset, grepl("bookkeeping", Algo)))
+  dset <- dset[order(dset$Size), ]
+
+  ## finally, add an "Index" attribute(, for further processing
+  dset <- cbind(dset, Index=seq(1, length(dset$Size))) # FIXME
 
-# finally, add an "Index" attribute(, for further processing
-xx <- cbind(xx, Index=c(1:length(xx$Size)))
+  #print(dset)
 
-# save the graphical parameters
-p <- par(no.readonly=TRUE)
+  ## 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))
 
-### TODO
-### - add some spacing between each size
-### - fill in empty rows (e.g. with large size)
-### - add a label telling the size
+  par(las=3)                           # always draw labels vertically
 
-par(mar=c(13, 4, 4, 4) + 0.1,           # change margins
-    mgp=c(11, 1, 0))
+  ## compute the time range: 0..max+20%
+  time_range <- c(0, range(dset$Conv_max)[2] * 1.2)
 
-par(las=3)                              # always draw labels vertically
+  ## 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)
 
-# compute the time range: 0..max+20%
-time_range <- c(0, range(xx$Conv_max)[2] * 1.2)
+  ## draw the time axis on the left
+  axis(2, labels=TRUE)
+  mtext("Simulated time (s)", side=2, line=2.5)
 
-# first draw the bars
-barplot(xx$Conv_max, axes=FALSE, col="red",
-        names=xx$Algo,
-        ylim=time_range)
-barplot(xx$Conv_avg, axes=FALSE, col="green",
-        add=TRUE)
-barplot(xx$Idle_avg, axes=FALSE, col="blue",
-        add=TRUE)
+  title(xlab="Algorithms")
 
-# draw the time axis on the left
-axis(2, labels=TRUE)
-mtext("Time (s)", side=2, line=2.5)
+  ## 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)
 
-title(xlab="Algorithms")
+  ## 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)
+  }
 
-# start a new graph, but drawn on the same device
+  ## 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)
+}
 
-# compute the data range
-x_data_range <- c(0.6, length(xx$Algo) + 0.4)
-data_range <- c(0, range(xx$Data_amnt)[2] * 1.04)
+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
+  rownames(dset.wide) <- sub("bookkeeping", "virtual", 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)
 
-# draw the data amnt line graph
-#par(new=TRUE)
-#plot(xx$Data_amnt, axes=FALSE, xlab="", type="b",
-#     xlim=x_data_range,
-#     yaxs="i", ylim=data_range)
+}
 
-for (alg in unique(xx$Algo)) {
-  print(alg);
-  yy <- subset(xx, Algo == alg)
-  par(new=TRUE)
-  plot(yy$Index, yy$Data_amnt, axes=FALSE, xlab="", type="b",
-       xlim=x_data_range,
-       yaxs="i", ylim=data_range)
+msg <- function(text,
+                wait = TRUE) {
+  if (wait)
+    readline("Press <Enter> to continue\n")
+  message(text)
 }
 
-# draw the data amnt axis on the right
-axis(4, labels=TRUE)
-mtext("Data amount (relative)", side=4, line=2.5)
+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")
 
-# finally, set title
-t <- paste0(xx$Mode[1], xx$Distrib[1], " / ", xx$Ratio[1], " / ",
-            xx$Platform[1], " / ", xx$Topo[1])
-title(main=t)
+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 the graphical parameters
-par(p)
+## restore default options
+options(scipen=osp)