47 lines
1.1 KiB
R
47 lines
1.1 KiB
R
library(ggplot2)
|
|
library(dplyr)
|
|
library(scales)
|
|
library(jsonlite)
|
|
|
|
args=commandArgs(trailingOnly=TRUE)
|
|
|
|
# Read the timetable from args[1]
|
|
input_file = "input.json"
|
|
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 nblocks and time
|
|
df = select(dataset, config.blocksize, config.gitBranch, time) %>%
|
|
rename(blocksize=config.blocksize, gitBranch=config.gitBranch) %>%
|
|
group_by(blocksize, gitBranch) %>%
|
|
mutate(mtime = median(time)) %>%
|
|
ungroup()
|
|
|
|
df$gitBranch = as.factor(df$gitBranch)
|
|
df$blocksize = as.factor(df$blocksize)
|
|
|
|
ppi=300
|
|
h=5
|
|
w=5
|
|
|
|
png("time.png", width=w*ppi, height=h*ppi, res=ppi)
|
|
#
|
|
## Create the plot with the normalized time vs nblocks
|
|
p = ggplot(df, aes(x=blocksize, y=time)) +
|
|
geom_point() +
|
|
geom_line(aes(y=mtime, group=gitBranch, color=gitBranch)) +
|
|
theme_bw() +
|
|
labs(x="Blocksize", y="Time (s)", title="FWI granularity",
|
|
subtitle=input_file) +
|
|
theme(plot.subtitle=element_text(size=8)) +
|
|
theme(legend.position = c(0.5, 0.88))
|
|
|
|
# Render the plot
|
|
print(p)
|
|
|
|
# Save the png image
|
|
dev.off()
|