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library(ggplot2)
library(patchwork)
df <- read.table("matrix_fasta_random_access.tsv", header = TRUE, sep = "\t")
#df1 <- df[which(df$tool != 'pyfasta' & df$tool != 'pyfastx_gzip' & df$tool != 'biopython'),]
#df2 <- df[which(df$tool == 'pyfasta' | df$tool == 'pyfastx_gzip' | df$tool == 'biopython'),]
p1 <-
ggplot(df, aes(
x = reorder(genome, size),
time,
colour = tool,
group = tool
)) +
geom_point(aes(size = memory)) +
geom_line() +
ylim(0, 1000) +
facet_grid(rows = vars(tool)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 30, hjust = 1),
axis.title.x = element_blank()) +
ylab("Elapsed time (s)") +
guides(colour = guide_legend(title = "Tools"),
size = guide_legend(title = "Memory (GB)"))
#p2 <-
# ggplot(df2, aes(
# x = reorder(genome, size),
# time,
# colour = tool,
# group = tool
# )) +
# geom_point(aes(size = memory)) +
# geom_line() +
#facet_grid(rows = vars(tool), scales="free_y") +
# theme_bw() +
# theme(axis.text.x = element_text(angle = 30, hjust = 1),
# axis.title.x = element_blank()) +
# ylab("Elapsed time (s)") +
# guides(colour = guide_legend(title = "Tools"),
# size = guide_legend(title = "Memory (GB)"))
df2 <- read.table("matrix_fasta_extract_subsequences.tsv", header=TRUE, sep="\t")
p2 <-
ggplot(df2, aes(
x = reorder(genome, size),
time,
colour = tool,
group = tool
)) +
geom_point(aes(size = memory)) +
geom_line() +
ylim(0, 50) +
facet_grid(rows = vars(tool)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 30, hjust = 1),
axis.title.x = element_blank()) +
ylab("Elapsed time (s)") +
guides(colour = guide_legend(title = "Tools"),
size = guide_legend(title = "Memory (GB)"))
df3 <- read.table("matrix_fastq_random_access.tsv", header = TRUE, sep = "\t")
p3 <-
ggplot(df3, aes(
x = reorder(file, fsize),
time,
colour = tool,
group = tool
)) +
geom_point(aes(size = memory)) +
geom_line() +
ylim(0, 500) +
facet_grid(rows = vars(tool)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 30, hjust = 1),
axis.title.x = element_blank()) +
ylab("Elapsed time (s)") +
guides(colour = guide_legend(title = "Tools"),
size = guide_legend(title = "Memory (GB)"))
pp <- p1 | p2 | p3
pp <- pp + plot_annotation(tag_levels = 'A')
show(pp)
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