101 lines
3.9 KiB
R
101 lines
3.9 KiB
R
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if (!endsWith(getwd(), "/sim")) {
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setwd("sim")
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}
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sim.plot <- function(file.prefix, date, to.file = FALSE) {
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# file.prefix <- "sim-ising-small"
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# # file.prefix <- "sim-normal"
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# date <- "20221012" # yyyymmdd, to match all "[0-9]{6}"
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time <- "[0-9]{4}" # HHMM, to match all "[0-9]{4}"
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colors <- c(
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PCA = "#a11414",
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HOPCA = "#2a62b6",
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TSIR = "#9313b9",
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GMLM = "#247407"
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)
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line.width <- 1.75
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margins <- c(5.1, 4.1, 4.1, 0.1)
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sim <- Reduce(rbind, Map(function(path) {
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df <- read.csv(path)
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df$n <- as.integer(tail(head(strsplit(path, "[-.]")[[1]], -1), 1))
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df
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}, list.files(".", pattern = paste0(
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"^", file.prefix, "-", date, "T", time, "-[0-9]+[.]csv$", collapse = ""
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))))
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stats <- aggregate(. ~ n, sim, mean)
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q75 <- aggregate(. ~ n, sim, function(x) quantile(x, 0.75))
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q25 <- aggregate(. ~ n, sim, function(x) quantile(x, 0.25))
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if (to.file) {
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width <- 720
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png(paste(file.prefix, "-", date, ".png", sep = ""),
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width = width, height = round((6 / 11) * width, -1),
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pointsize = 12)
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}
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layout(mat = matrix(c(
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1, 2,
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3, 3
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), 2, 2, byrow = TRUE),
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widths = c(1, 1),
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heights = c(12, 1), respect = FALSE)
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# layout.show(3)
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with(stats, {
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par(mar = margins)
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plot(range(n), 0:1,
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type = "n", bty = "n", main = "Subspace Distance",
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xlab = "Sample Size", ylab = "Error")
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lines(n, dist.subspace.gmlm, col = colors["GMLM"], lwd = line.width)
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lines(n, dist.subspace.hopca, col = colors["HOPCA"], lwd = line.width)
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lines(n, dist.subspace.pca, col = colors["PCA"], lwd = line.width)
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lines(n, dist.subspace.tsir, col = colors["TSIR"], lwd = line.width)
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xn <- c(q75$n, rev(q25$n))
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polygon(x = xn, y = c(q75$dist.subspace.gmlm, rev(q25$dist.subspace.gmlm)),
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col = adjustcolor(colors["GMLM"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$dist.subspace.hopca, rev(q25$dist.subspace.hopca)),
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col = adjustcolor(colors["HOPCA"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$dist.subspace.pca, rev(q25$dist.subspace.pca)),
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col = adjustcolor(colors["PCA"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$dist.subspace.tsir, rev(q25$dist.subspace.tsir)),
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col = adjustcolor(colors["TSIR"], alpha.f = 0.3), border = NA)
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})
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with(stats, {
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par(mar = margins)
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plot(range(n), 0:1,
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type = "n", bty = "n", main = "RMSE (Prediction Error)",
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xlab = "Sample Size", ylab = "Error")
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xn <- c(q75$n, rev(q25$n))
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polygon(x = xn, y = c(q75$error.pred.gmlm, rev(q25$error.pred.gmlm)),
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col = adjustcolor(colors["GMLM"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$error.pred.hopca, rev(q25$error.pred.hopca)),
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col = adjustcolor(colors["HOPCA"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$error.pred.pca, rev(q25$error.pred.pca)),
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col = adjustcolor(colors["PCA"], alpha.f = 0.3), border = NA)
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polygon(x = xn, y = c(q75$error.pred.tsir, rev(q25$error.pred.tsir)),
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col = adjustcolor(colors["TSIR"], alpha.f = 0.3), border = NA)
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lines(n, error.pred.gmlm, col = colors["GMLM"], lwd = line.width)
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lines(n, error.pred.hopca, col = colors["HOPCA"], lwd = line.width)
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lines(n, error.pred.pca, col = colors["PCA"], lwd = line.width)
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lines(n, error.pred.tsir, col = colors["TSIR"], lwd = line.width)
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})
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par(mar = rep(0, 4))
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plot(1:2, 1:2, type = "n", bty = "n", axes = FALSE, xlab = "", ylab = "")
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legend("center", legend = names(colors), col = colors, lwd = line.width,
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lty = 1, bty = "n", horiz = TRUE)
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if (to.file) {
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dev.off()
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}
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}
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sim.plot("sim-ising-small", "20221012", TRUE)
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sim.plot("sim-normal", "20221012", TRUE)
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