Define a function for plotting.

diff --git a/supercomp11/data/script.r b/supercomp11/data/script.r
index f15d382fe81c87571b7ab321855b5276fd0a48a0..9694aba5fc9b72843f4768d3b36b148c3e8b5784 100644 (file)
--- a/supercomp11/data/script.r
+++ b/supercomp11/data/script.r
@@ -1,92 +1,113 @@
-# Usage: launch R, and then: source("script.r")
+## Usage: launch R, and then: source("script.r")

 
 

-# load dataset (variable is "ds")
+## 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
+## 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 == 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") {

 
 

-# finally, add an "Index" attribute(, for further processing
-xx <- cbind(xx, Index=c(1:length(xx$Size)))
+  ## extract desired data
+  dset <- subset(dset,
+                 Mode == draw_mode & Distrib == draw_distrib &
+                 Ratio == draw_ratio &
+                 Platform == draw_platform & Topo == draw_topo)

 
 

-# save the graphical parameters
-p <- par(no.readonly=TRUE)
+  ## 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
 
 
 ### 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(mar=c(13, 4, 4, 4) + 0.1,         # change margins
+      mgp=c(11, 1, 0))
+
+  par(las=3)                           # always draw labels vertically

 
 

-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)

 
 

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

 
 

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

 
 

-# draw the time axis on the left
-axis(2, labels=TRUE)
-mtext("Time (s)", side=2, line=2.5)
+  title(xlab="Algorithms")

 
 

-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)

 
 

-# start a new graph, but drawn on the same device
+  ## 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)
+  }

 
 

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

 
 

-# draw the data amnt line graph
-#par(new=TRUE)
-#plot(xx$Data_amnt, axes=FALSE, xlab="", type="b",
-#     xlim=x_data_range,
-#     yaxs="i", ylim=data_range)
+  ## finally, set title
+  t <- paste0(dset$Mode[1], dset$Distrib[1], " / ", dset$Ratio[1], " / ",
+              dset$Platform[1], " / ", dset$Topo[1])
+  title(main=t)
+
+  ## restore the graphical parameters
+  par(p)
+
+}

 
 

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

 
 

-# finally, set title
-t <- paste0(xx$Mode[1], xx$Distrib[1], " / ", xx$Ratio[1], " / ",
-            xx$Platform[1], " / ", xx$Topo[1])
-title(main=t)
+msg("Second test, with algorithms \"bookkeeping\"...");
+draw(subset(ds, grepl("[lt]_bookkeeping", Algo)))

 
 

-# restore the graphical parameters
-par(p)
+msg("Third test, with all algorithms...");
+draw()