if (!endsWith(getwd(), "/sim")) {
    setwd("sim")
}

sim.plot <- function(file.prefix, date, to.file = FALSE) {

    # file.prefix <- "sim-ising-small"
    # # file.prefix <- "sim-normal"
    # date <- "20221012"  # yyyymmdd, to match all "[0-9]{6}"
    time <- "[0-9]{4}"  # HHMM,     to match all "[0-9]{4}"
    colors <- c(
        PCA   = "#a11414",
        HOPCA = "#2a62b6",
        TSIR  = "#9313b9",
        GMLM  = "#247407"
    )
    line.width <- 1.75
    margins <- c(5.1, 4.1, 4.1, 0.1)

    sim <- Reduce(rbind, Map(function(path) {
        df <- read.csv(path)
        df$n <- as.integer(tail(head(strsplit(path, "[-.]")[[1]], -1), 1))
        df
    }, list.files(".", pattern = paste0(
        "^", file.prefix, "-", date, "T", time, "-[0-9]+[.]csv$", collapse = ""
    ))))

    stats <- aggregate(. ~ n, sim, mean)
    q75 <- aggregate(. ~ n, sim, function(x) quantile(x, 0.75))
    q25 <- aggregate(. ~ n, sim, function(x) quantile(x, 0.25))

    if (to.file) {
        width <- 720
        png(paste(file.prefix, "-", date, ".png", sep = ""),
            width = width, height = round((6 / 11) * width, -1),
            pointsize = 12)
    }

    layout(mat = matrix(c(
        1, 2,
        3, 3
    ), 2, 2, byrow = TRUE),
        widths = c(1, 1),
        heights = c(12, 1), respect = FALSE)
    # layout.show(3)

    with(stats, {
        par(mar = margins)
        plot(range(n), 0:1,
            type = "n", bty = "n", main = "Subspace Distance",
            xlab = "Sample Size", ylab = "Error")
        lines(n, dist.subspace.gmlm,  col = colors["GMLM"],  lwd = line.width)
        lines(n, dist.subspace.hopca, col = colors["HOPCA"], lwd = line.width)
        lines(n, dist.subspace.pca,   col = colors["PCA"],   lwd = line.width)
        lines(n, dist.subspace.tsir,  col = colors["TSIR"],  lwd = line.width)

        xn <- c(q75$n, rev(q25$n))
        polygon(x = xn, y = c(q75$dist.subspace.gmlm, rev(q25$dist.subspace.gmlm)),
            col = adjustcolor(colors["GMLM"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$dist.subspace.hopca, rev(q25$dist.subspace.hopca)),
            col = adjustcolor(colors["HOPCA"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$dist.subspace.pca, rev(q25$dist.subspace.pca)),
            col = adjustcolor(colors["PCA"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$dist.subspace.tsir, rev(q25$dist.subspace.tsir)),
            col = adjustcolor(colors["TSIR"], alpha.f = 0.3), border = NA)
    })

    with(stats, {
        par(mar = margins)
        plot(range(n), 0:1,
            type = "n", bty = "n", main = "RMSE (Prediction Error)",
            xlab = "Sample Size", ylab = "Error")
        xn <- c(q75$n, rev(q25$n))
        polygon(x = xn, y = c(q75$error.pred.gmlm, rev(q25$error.pred.gmlm)),
            col = adjustcolor(colors["GMLM"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$error.pred.hopca, rev(q25$error.pred.hopca)),
            col = adjustcolor(colors["HOPCA"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$error.pred.pca, rev(q25$error.pred.pca)),
            col = adjustcolor(colors["PCA"], alpha.f = 0.3), border = NA)
        polygon(x = xn, y = c(q75$error.pred.tsir, rev(q25$error.pred.tsir)),
            col = adjustcolor(colors["TSIR"], alpha.f = 0.3), border = NA)
        lines(n, error.pred.gmlm,  col = colors["GMLM"],  lwd = line.width)
        lines(n, error.pred.hopca, col = colors["HOPCA"], lwd = line.width)
        lines(n, error.pred.pca,   col = colors["PCA"],   lwd = line.width)
        lines(n, error.pred.tsir,  col = colors["TSIR"],  lwd = line.width)
    })

    par(mar = rep(0, 4))
    plot(1:2, 1:2, type = "n", bty = "n", axes = FALSE, xlab = "", ylab = "")
    legend("center", legend = names(colors), col = colors, lwd = line.width,
        lty = 1, bty = "n", horiz = TRUE)

    if (to.file) {
        dev.off()
    }
}

sim.plot("sim-ising-small", "20221012", TRUE)
sim.plot("sim-normal", "20221012", TRUE)