From 43991e9173eb725611f4edcede3faf10386fd8f9 Mon Sep 17 00:00:00 2001
From: Rodrigo Arias Mallo <rodrigo.arias@bsc.es>
Date: Tue, 27 Oct 2020 10:49:00 +0100
Subject: [PATCH] nbody: plot nblocks in test

---
 garlic/fig/nbody/test.R | 19 +++++++++----------
 1 file changed, 9 insertions(+), 10 deletions(-)

diff --git a/garlic/fig/nbody/test.R b/garlic/fig/nbody/test.R
index 21cb225..3db1610 100644
--- a/garlic/fig/nbody/test.R
+++ b/garlic/fig/nbody/test.R
@@ -22,7 +22,6 @@ df = select(dataset, config.nblocks, config.hw.cpusPerSocket, time) %>%
 
 df = df %>% mutate(blocksPerCpu = nblocks / cpusPerSocket)
 df$nblocks = as.factor(df$nblocks)
-df$blocksPerCpuFactor = as.factor(df$blocksPerCpu)
 
 # Normalize the time by the median
 D=group_by(df, nblocks) %>%
@@ -42,10 +41,10 @@ png("box.png", width=w*ppi, height=h*ppi, res=ppi)
 #
 #
 # Create the plot with the normalized time vs nblocks
-p = ggplot(data=D, aes(x=blocksPerCpuFactor, y=tnorm)) +
+p = ggplot(data=D, aes(x=nblocks, y=tnorm)) +
 
 	# Labels
-	labs(x="Blocks/CPU", y="Normalized time",
+	labs(x="Blocks", y="Normalized time",
               title=sprintf("Nbody normalized time. Particles=%d", particles), 
               subtitle=input_file) +
 
@@ -56,13 +55,13 @@ p = ggplot(data=D, aes(x=blocksPerCpuFactor, y=tnorm)) +
 	#theme_bw() +
 
 	# Add the maximum allowed error lines
-	geom_hline(yintercept=c(-0.01, 0.01),
-		linetype="dashed", color="red") +
+	#geom_hline(yintercept=c(-0.01, 0.01),
+	#	linetype="dashed", color="red") +
 
 	# Draw boxplots
 	geom_boxplot() +
 
-	scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
+	#scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
 
 	theme_bw() +
 
@@ -84,17 +83,17 @@ dev.off()
 png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
 #
 ## Create the plot with the normalized time vs nblocks
-p = ggplot(D, aes(x=blocksPerCpuFactor, y=time)) +
+p = ggplot(D, aes(x=nblocks, y=time)) +
 
-	labs(x="Blocks/CPU", y="Time (s)",
+	labs(x="Blocks", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
               subtitle=input_file) +
 	theme_bw() +
 	theme(plot.subtitle=element_text(size=8)) +
 	theme(legend.position = c(0.5, 0.88)) +
 
-	geom_point(shape=21, size=3) +
-	scale_y_continuous(trans=log2_trans())
+	geom_point(shape=21, size=3) # +
+	#scale_y_continuous(trans=log2_trans())
 
 # Render the plot
 print(p)