From cc929d7db160878fc22971b62613c2ec821c654a Mon Sep 17 00:00:00 2001 From: "Julian M. Kunkel" Date: Tue, 25 Aug 2020 18:00:28 +0100 Subject: [PATCH] Added figures. --- fig/progress_4296426-out-boxplot.png | Bin 0 -> 73689 bytes fig/progress_4296426-out-cummulative.png | Bin 0 -> 153887 bytes fig/progress_5024292-out-boxplot.png | Bin 0 -> 77467 bytes fig/progress_5024292-out-cummulative.png | Bin 0 -> 193317 bytes fig/progress_7488914-out-boxplot.png | Bin 0 -> 77798 bytes fig/progress_7488914-out-cummulative.png | Bin 0 -> 130134 bytes paper/main.tex | 54 ++++++++++++++--------- scripts/analyse-all.sh | 7 +++ scripts/plot-performance-clustering.R | 21 +++++++++ scripts/plot-performance.R | 25 ++++++----- scripts/plot.R | 4 +- 11 files changed, 76 insertions(+), 35 deletions(-) create mode 100644 fig/progress_4296426-out-boxplot.png create mode 100644 fig/progress_4296426-out-cummulative.png create mode 100644 fig/progress_5024292-out-boxplot.png create mode 100644 fig/progress_5024292-out-cummulative.png create mode 100644 fig/progress_7488914-out-boxplot.png create 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zljp&EmGkiMfMZTZ=Dvpu$}AL^mnF5htWe&<)sT|?`;HFXQ4`eL4IfMfL z9zOX0_*-RDSmZCg`Hv9gCOR6X|D0=h{olh3qy9a?@ZZxAU;I1t`QN|w|Eed@xUuEl XE4A27Sti$r4J9Y7d?8!v^4% filter(min_sim %in% c(0.1, 0.5, 0.99)) +e$percent = paste("SIM =", as.factor(round(e$min_sim*100,0)), " %") + +# Development when adding more jobs +ggplot(e, aes(x=jobs_done, y=elapsed, color=alg_name)) + geom_point() + facet_grid(percent ~ .) + ylab("Cummulative runtime in s") + xlab("Jobs processed") + scale_y_log10() + theme(legend.position = "bottom") +ggsave("fig/runtime-cummulative.png", width=6, height=4.5) + +# Bar chart for the maximum +e = data %>% filter(jobs_done >= (jobs_total - 9998)) +e$percent = as.factor(round(e$min_sim*100,0)) +ggplot(e, aes(y=elapsed, x=percent, fill=alg_name)) + geom_bar(stat="identity") + facet_grid(. ~ alg_name, switch = 'y') + scale_y_log10() + theme(legend.position = "none") + ylab("Runtime in s") + xlab("Minimum similarity in %") + geom_text(aes(label = round(elapsed,0), angle = 90, y=0*(elapsed)+20)) +ggsave("fig/runtime-overview.png", width=7, height=2) diff --git a/scripts/plot-performance.R b/scripts/plot-performance.R index 9315e33..86d2678 100755 --- a/scripts/plot-performance.R +++ b/scripts/plot-performance.R @@ -3,19 +3,20 @@ library(ggplot2) library(dplyr) require(scales) -# Plot the performance numbers of the clustering +args = commandArgs(trailingOnly = TRUE) +file = "datasets/progress_4296426.csv" # for manual execution +file = args[1] +prefix = args[2] -data = read.csv("datasets/clustering_progress.csv") -e = data %>% filter(min_sim %in% c(0.1, 0.5, 0.99)) -e$percent = paste("SIM =", as.factor(round(e$min_sim*100,0)), " %") +# Plot the performance numbers of the analysis +data = read.csv(file) + +e = data %>% filter(jobs_done >= (jobs_total - 9998)) +e$time_per_100k = e$elapsed / (e$jobs_done / 100000) +ggplot(e, aes(alg_name, time_per_100k, fill=alg_name)) + geom_boxplot() + theme(legend.position=c(0.2, 0.7)) + xlab("Algorithm") + ylab("Runtime in s per 100k jobs") + stat_summary(aes(label=round(..y..,0)), position = position_nudge(x = 0, y = 250), fun=mean, geom="text", size=4) +ggsave(paste(prefix, "-boxplot.png", sep=""), width=5, height=4) # Development when adding more jobs -ggplot(e, aes(x=jobs_done, y=elapsed, color=alg_name)) + geom_point() + facet_grid(percent ~ .) + ylab("Cummulative runtime in s") + xlab("Jobs processed") + scale_y_log10() + theme(legend.position = "bottom") -ggsave("fig/runtime-cummulative.png", width=6, height=4.5) - -# Bar chart for the maximum -e = data %>% filter(jobs_done >= (jobs_total - 9998)) -e$percent = as.factor(round(e$min_sim*100,0)) -ggplot(e, aes(y=elapsed, x=percent, fill=alg_name)) + geom_bar(stat="identity") + facet_grid(. ~ alg_name, switch = 'y') + scale_y_log10() + theme(legend.position = "none") + ylab("Runtime in s") + xlab("Minimum similarity in %") + geom_text(aes(label = round(elapsed,0), angle = 90, y=0*(elapsed)+20)) -ggsave("fig/runtime-overview.png", width=7, height=2) +ggplot(data, aes(x=jobs_done, y=elapsed, color=alg_name)) + geom_point() + ylab("Cummulative runtime in s") + xlab("Jobs processed") + theme(legend.position = "bottom") #+ scale_x_log10() + scale_y_log10() +ggsave(paste(prefix, "-cummulative.png", sep=""), width=6, height=4.5) diff --git a/scripts/plot.R b/scripts/plot.R index c8ff172..e66316c 100755 --- a/scripts/plot.R +++ b/scripts/plot.R @@ -113,8 +113,8 @@ for (l1 in levels(data$alg_name)){ print(res.intersect) # Plot heatmap about intersection -ggplot(tbl.intersect, aes(first, second, fill=intersect)) + geom_tile() + geom_text(aes(label = round(intersect, 1))) + scale_fill_gradientn(colours = rev(plotcolors)) + xlab("") + ylab("") -ggsave("intersection-heatmap.png", width=6, height=5) +ggplot(tbl.intersect, aes(first, second, fill=intersect)) + geom_tile() + geom_text(aes(label = round(intersect, 1))) + scale_fill_gradientn(colours = rev(plotcolors)) + xlab("") + ylab("") + theme(legend.position = "bottom", legend.title = element_blank()) +ggsave("intersection-heatmap.png", width=4.5, height=4.5) # Collect the metadata of all jobs in a new table res.jobs = tibble()

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