WIP: postprocessing pipeline

Now each run is executed in a independent folder

garlic/fig/nbody/jemalloc.R

@@ -0,0 +1,104 @@
+library(ggplot2)
+library(dplyr)
+library(scales)
+library(jsonlite)
+
+args=commandArgs(trailingOnly=TRUE)
+
+# Read the timetable from args[1]
+input_file = "timetable.json.gz"
+if (length(args)>0) { input_file = args[1] }
+
+# Load the dataset in NDJSON format
+dataset = jsonlite::stream_in(file(input_file)) %>%
+	jsonlite::flatten()
+
+# We only need the cpu bind, blocksize and time
+df = select(dataset, config.enableJemalloc, config.blocksize, time) %>%
+	rename(blocksize=config.blocksize,
+	       jemalloc=config.enableJemalloc)
+
+# Use the blocksize as factor
+df$blocksize = as.factor(df$blocksize)
+df$jemalloc = as.factor(df$jemalloc)
+
+# Split by malloc variant
+D=df %>% group_by(jemalloc, blocksize) %>%
+	mutate(tnorm = time / median(time) - 1)
+
+bs_unique = unique(df$blocksize)
+nbs=length(bs_unique)
+
+
+print(D)
+
+ppi=300
+h=5
+w=5
+
+png("box.png", width=w*ppi, height=h*ppi, res=ppi)
+#
+#
+#
+# Create the plot with the normalized time vs blocksize
+p = ggplot(data=D, aes(x=blocksize, y=tnorm)) +
+
+	# Labels
+	labs(x="Block size", y="Normalized time",
+              title="Nbody normalized time",
+              subtitle=input_file) +
+
+	# Center the title
+	#theme(plot.title = element_text(hjust = 0.5)) +
+
+	# Black and white mode (useful for printing)
+	#theme_bw() +
+
+	# Add the maximum allowed error lines
+	geom_hline(yintercept=c(-0.01, 0.01),
+		linetype="dashed", color="red") +
+
+	# Draw boxplots
+	geom_boxplot(aes(fill=freeCpu)) +
+
+#	# Use log2 scale in x
+#	scale_x_continuous(trans=log2_trans(),
+#			   breaks=bs_unique) +
+#
+	scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
+
+	theme_bw() +
+
+	theme(plot.subtitle=element_text(size=10)) +
+
+	theme(legend.position = c(0.85, 0.85)) #+
+
+	# Place each variant group in one separate plot
+
+
+
+# Render the plot
+print(p)
+
+## Save the png image
+dev.off()
+#
+png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
+#
+## Create the plot with the normalized time vs blocksize
+p = ggplot(D, aes(x=blocksize, y=time, color=freeCpu)) +
+
+	labs(x="Block size", y="Time (s)",
+              title="Nbody granularity",
+              subtitle=input_file) +
+	theme_bw() +
+
+	geom_point(shape=21, size=3) +
+	#scale_x_continuous(trans=log2_trans()) +
+	scale_y_continuous(trans=log2_trans())
+
+# Render the plot
+print(p)
+
+# Save the png image
+dev.off()