#!/usr/bin/env Rscript

library(ggplot2)
library(reshape2)
library(pander)

data <- read.csv("results/results.csv", check.names=FALSE)

# Reorder columns for readability.
col_order <- c("Least-squares slope", "Theil-Sen slope",
               "Mean", "Median of means",
               "Minimum of means", "Quartile 1 of means", "Quartile 3 of means")
data <- data[, col_order]

molten <- melt(data)

# Assign categories to variables.
molten$type <- factor(
    "This should never be visible",
    levels=c("Central tendency", "Regression", "Other", "This should never be visible"))
molten <- within(molten, type[variable == "Least-squares slope" | variable == "Theil-Sen slope"] <- "Regression")
molten <- within(molten, type[variable == "Mean" | variable == "Median of means"] <- "Central tendency")
molten <- within(molten, type[variable == "Quartile 1 of means" | variable == "Quartile 3 of means" | variable == "Minimum of means"] <- "Other")

# Draw densities.
plot <- ggplot(molten, aes(x=value, color=variable)) +
    geom_density(adjust=0.5) +
    labs(x="Time [s]", y="Number of benchmarks (smoothed)", color="") +
    facet_wrap("type", scales="fixed", ncol=1)
ggsave("results/density.pdf", plot, device=cairo_pdf, width=8, height=6)

# Draw boxplots.
plot <- ggplot(molten, aes(x=variable, y=value)) +
    geom_boxplot() +
    labs(x="Statistic", y="Time [s]") +
    theme(axis.text.x=element_text(angle=25, hjust=1))
png(filename="results/boxplot.png", type="cairo", width=1100, height=1100, units="px", res=200)
print(plot)
dev.off()

# Data range as a single number (instead of vector of min and max).
range_num <- function(data) {
    return(diff(range(data)))
}

# Summarize the spread of the data in a table.
df <- data.frame()
df[ncol(data),] <- NA
rownames(df) <- names(data)
iqr_rel <- apply(data, 2, IQR) / apply(data, 2, median)
df$`IQR/Median` <- sprintf("%.1f%%", unlist(iqr_rel * 100))
range_rel <- apply(data, 2, range_num) / apply(data, 2, median)
df$`Range/Median` <- sprintf("%.1f%%", unlist(range_rel * 100))
table <- pandoc.table.return(
    df, style="rmarkdown", justify=c("right", "left", "left"), emphasize.rownames=FALSE)
handle <- file("results/summary.md")
writeLines(table, handle)
close(handle)