bscpkgs/garlic/fig/fwi/granularity.R

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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
####################################################################
### Line Graph
####################################################################
png("mtime.png", width=w*ppi, height=h*ppi, res=ppi)
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## Create the plot with the normalized time vs nblocks
p = ggplot(df, aes(x = blocksize, y=mtime, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
theme_bw() +
labs(x="Blocksize", y="Median 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()
####################################################################
### Line Graph
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####################################################################
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, group=gitBranch, color=gitBranch)) +
geom_point() +
geom_line() +
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))
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# Render the plot
print(p)
# Save the png image
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dev.off()