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heat: add figure with heatmap

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This commit is contained in:
Rodrigo Arias 2021-03-05 16:21:13 +01:00
parent 363700eb9a
commit 29d7245135
1 changed files with 36 additions and 11 deletions
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47
garlic/fig/heat/test.R
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@ -15,16 +15,20 @@ dataset = jsonlite::stream_in(file(input_file)) %>%
# We only need the nblocks and time # We only need the nblocks and time
df = select(dataset, config.bsx, time) %>% df = select(dataset, config.cbs, config.rbs, time) %>%
rename(bsx=config.bsx) rename(cbs=config.cbs, rbs=config.rbs)
df$bsx = as.factor(df$bsx) df$cbs = as.factor(df$cbs)
df$rbs = as.factor(df$rbs)
# Normalize the time by the median # Normalize the time by the median
D=group_by(df, bsx) %>% df=group_by(df, cbs, rbs) %>%
mutate(tnorm = time / median(time) - 1) mutate(mtime = median(time)) %>%
mutate(tnorm = time / mtime - 1) %>%
print(D) mutate(logmtime = log(mtime)) %>%
ungroup() %>%
filter(between(mtime, mean(time) - (1 * sd(time)),
mean(time) + (1 * sd(time))))
ppi=300 ppi=300
h=5 h=5
@ -35,10 +39,10 @@ png("box.png", width=w*ppi, height=h*ppi, res=ppi)
# #
# #
# Create the plot with the normalized time vs nblocks # Create the plot with the normalized time vs nblocks
p = ggplot(data=D, aes(x=bsx, y=tnorm)) + p = ggplot(data=df, aes(x=cbs, y=tnorm)) +
# Labels # Labels
labs(x="bsx", y="Normalized time", labs(x="cbs", y="Normalized time",
title=sprintf("Heat normalized time"), title=sprintf("Heat normalized time"),
subtitle=input_file) + subtitle=input_file) +
@ -75,9 +79,9 @@ dev.off()
png("scatter.png", width=w*ppi, height=h*ppi, res=ppi) png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
# #
## Create the plot with the normalized time vs nblocks ## Create the plot with the normalized time vs nblocks
p = ggplot(D, aes(x=bsx, y=time)) + p = ggplot(df, aes(x=cbs, y=time, linetype=rbs, group=rbs)) +
labs(x="bsx", y="Time (s)", labs(x="cbs", y="Time (s)",
title=sprintf("Heat granularity"), title=sprintf("Heat granularity"),
subtitle=input_file) + subtitle=input_file) +
theme_bw() + theme_bw() +
@ -85,6 +89,7 @@ p = ggplot(D, aes(x=bsx, y=time)) +
theme(legend.position = c(0.5, 0.88)) + theme(legend.position = c(0.5, 0.88)) +
geom_point(shape=21, size=3) + geom_point(shape=21, size=3) +
geom_line(aes(y=mtime)) +
#scale_x_continuous(trans=log2_trans()) + #scale_x_continuous(trans=log2_trans()) +
scale_y_continuous(trans=log2_trans()) scale_y_continuous(trans=log2_trans())
@ -93,3 +98,23 @@ print(p)
# Save the png image # Save the png image
dev.off() dev.off()
png("heatmap.png", width=w*ppi, height=h*ppi, res=ppi)
#
## Create the plot with the normalized time vs nblocks
p = ggplot(df, aes(x=cbs, y=rbs, fill=logmtime)) +
geom_raster() +
scale_fill_gradient(high="black", low="white") +
coord_fixed() +
theme_bw() +
theme(plot.subtitle=element_text(size=8)) +
labs(x="cbs", y="rbs",
title=sprintf("Heat granularity"),
subtitle=input_file)
# Render the plot
print(p)
# Save the png image
dev.off()