diff options
| -rw-r--r-- | plot.R | 104 |
1 files changed, 52 insertions, 52 deletions
@@ -58,53 +58,6 @@ plot.measures <- function(datasets, techniques, measures, output.dir, n.iter=30) } } -# Plots relative improvements for all techniques for a given measure and -# dataset. -plot.ri.measure <- function(ds, techniques, output.dir, measure, n.iter=30) { - df <- data.frame() - scale.labels <- c() - - #r.cp <- read.table(file.path(output.dir, ds$name, paste("r-cp-", measure$name, ".tbl", sep="")))$V1 - for (tech in techniques) { - r <- read.table(file.path(output.dir, ds$name, tech$name, paste("r-", measure$name, ".tbl", sep="")))$V1 - df <- rbind(df, data.frame(name=tech$name.pretty, - type=paste("Y", tech$name, ")", sep=""), - V1=r) - ) - - scale.labels <- c(scale.labels, tech$name.pretty) - } - - p <- ggplot(df) + - background_grid(major="xy", minor="none") + - theme(legend.position="none") + - labs(x="", y=measure$name.pretty) + - geom_boxplot(aes(type, V1, fill=name)) + - scale_fill_brewer(palette="Set1", guide=guide_legend(title="")) + - scale_y_continuous(limits=c(min(1, min(df$V1)), max(1, max(df$V1)))) + - scale_x_discrete(labels=scale.labels) - - fname <- file.path(output.dir, "plots", ds$name, paste("r-", measure$name, ".pdf", sep="")) - loginfo("Saving plot: %s", fname) - save_plot(fname, p, base_aspect_ratio=2) -} - -# Plot boxplots of all techniques measures per dataset. -plot.ri <- function(datasets, techniques, measures, output.dir, n.iter=30) { - dir.create.safe(file.path(output.dir, "plots")) - - for (ds in datasets) { - dir.create.safe(file.path(output.dir, "plots", ds$name)) - for (measure in measures) { - if (is.null(ds$labels.file) && measure$name == "silhouette") { - next - } - - plot.ri.measure(ds, techniques, output.dir, measure, n.iter) - } - } -} - # Same as above, but averages over all datasets. plot.averages <- function(datasets, techniques, measures, output.dir, n.iter=30) { dir.create.safe(file.path(output.dir, "plots")) @@ -215,10 +168,10 @@ plot.ci.measure <- function(measure, datasets, techniques, output.dir, n.iter=30 } base.path <- file.path(output.dir, ds$name, tech$name) - fname <- file.path(base.path, paste(measure$name, "Y.tbl", sep="-")) - Y.measure <- read.table(fname)$V1 - fname <- file.path(base.path, paste(measure$name, "Ym.tbl", sep="-")) - Ym.measure <- read.table(fname)$V1 + fname <- paste(measure$name, "Y.tbl", sep="-") + Y.measure <- read.table(file.path(base.path, fname))$V1 + fname <- paste(measure$name, "Ym.tbl", sep="-") + Ym.measure <- read.table(file.path(base.path, fname))$V1 measure.df <- rbind(measure.df, data.frame(tech=tech$name.pretty, dataset=ds$name.pretty, y=Ym.measure - Y.measure)) @@ -259,6 +212,54 @@ plot.ci <- function(datasets, techniques, measures, output.dir, n.iter=30) { } } +# Plot a single scatterplot of techniques and datasets, where x axis is the +# measure anipulation. +plot.evo.measure <- function(measure, datasets, techniques, output.dir) { + measure.df <- data.frame() + for (ds in datasets) { + if (is.null(ds$labels.file) && measure$name == "silhouette") { + next + } + for (tech in techniques) { + base.path <- file.path(output.dir, ds$name, tech$name) + fname <- paste(measure$name, "Ys-evo.tbl", sep="-") + Ys.measure <- read.table(file.path(base.path, fname))$V1 + fname <- paste(measure$name, "Y-evo.tbl", sep="-") + Y.measure <- read.table(file.path(base.path, fname))$V1 + measure.df <- rbind(measure.df, data.frame(tech=tech$name.pretty, + dataset=ds$name.pretty, + x=Ys.measure, + y=Y.measure)) + } + } + + p <- ggplot(measure.df) + + background_grid(major="xy", minor="none") + + theme(legend.position="right") + + labs(x=paste(measure$name.pretty, "(Ys)", sep=" "), + y=paste(measure$name.pretty, "(Y)", sep=" ")) + + geom_point(aes(x=x, y=y, color=tech, shape=dataset), alpha=0.8, size=3) + + geom_path(aes(x=x, y=y, color=tech, group=tech), arrow=arrow(angle=10, length=unit(0.15, "in"), type="closed")) + scale_color_brewer(palette="Set1", guide=guide_legend(title="Technique")) + + scale_shape(guide=guide_legend(title="Dataset")) + + fname <- file.path(output.dir, "plots", paste(measure$name, "-evo", ".pdf", sep="")) + loginfo("Saving plot: %s", fname) + save_plot(fname, p, base_aspect_ratio=1.5) + + p +} + +# This function runs the scatterplot function above for all measures +plot.evo <- function(datasets, techniques, measures, output.dir) { + dir.create.safe(file.path(output.dir, "plots")) + + for (measure in measures) { + p <- plot.evo.measure(measure, datasets, techniques, output.dir) + } +} + + # Experiment configuration # Defines: datasets, techniques, measures, output.dir source("config.R") @@ -274,5 +275,4 @@ addHandler(writeToFile, plot.measures(datasets, techniques, measures, output.dir) plot.averages(datasets, techniques, measures, output.dir) plot.scatter(datasets, techniques, measures, output.dir) -plot.ri(datasets, techniques, measures, output.dir) plot.ci(datasets, techniques, measures, output.dir) |