Nothing
# This function is mainly for testing purposes and will create on Voronoi diagram
# for each saved MCMC iteration
voronoi.diagram <- function(mcmcpath, dimns, longlat, plot.params,
post.draws = 1, is.mrates = TRUE) {
message("Plotting Voronoi tessellation of estimated effective rates")
if (is.mrates) {
log_scale <- plot.params$m.log_scale
} else {
log_scale <- plot.params$q.log_scale
}
voronoi <- read.voronoi(mcmcpath, longlat, is.mrates, log_scale)
rates <- voronoi$rates
tiles <- voronoi$tiles
xseed <- voronoi$xseed
yseed <- voronoi$yseed
# Choose one saved posterior draw at random
niters <- length(tiles)
riter <- sample(seq(niters), 1)
message(mcmcpath)
message("Draw ", riter, " (out of ", niters, ")")
eems.colors <- plot.params$eems.colors
num.levels <- length(eems.colors)
if (is.mrates) {
eems.levels <- eems.colscale(rates, num.levels, plot.params$m.colscale)
} else {
eems.levels <- eems.colscale(rates, num.levels, plot.params$q.colscale)
}
n.levels <- length(eems.levels)
max.levels <- max(eems.levels)
min.levels <- min(eems.levels)
# Jump over stored parameters for draws 1 to (riter - 1)
skip <- sum(tiles[riter:1][-1])
now.tiles <- tiles[riter]
now.rates <- rates[(skip + 1):(skip + now.tiles)]
now.xseed <- xseed[(skip + 1):(skip + now.tiles)]
now.yseed <- yseed[(skip + 1):(skip + now.tiles)]
# Standardize the log-transformed rates, without taking into account
# the relative size of the tiles (this is hard to do without a grid)
now.rates <- now.rates - mean(now.rates)
now.rates <- ifelse(now.rates > max.levels, max.levels, now.rates)
now.rates <- ifelse(now.rates < min.levels, min.levels, now.rates)
plot(0, 0,
type = "n", xlim = dimns$xlim, ylim = dimns$ylim, asp = 1,
axes = FALSE, xlab = "", ylab = "", main = ""
)
if (now.tiles == 1) {
# There is only one tile
tile.color <- eems.colors[round(n.levels / 2)]
polygon(dimns$xlim, dimns$ylim, col = tile.color, border = "white")
} else {
# Plot each tile in turn (as a polygon)
Voronoi <- deldir::deldir(now.xseed, now.yseed, rw = c(dimns$xlim, dimns$ylim))
tilelist <- deldir::tile.list(Voronoi)
for (c in 1:now.tiles) {
tile.color <- eems.colors[findInterval(now.rates[c], eems.levels, all.inside = TRUE)]
polygon(tilelist[[c]]$x, tilelist[[c]]$y, col = tile.color, border = "white")
}
filled.contour.graph(mcmcpath, longlat, plot.params)
}
if (plot.params$add.seeds) {
points(now.xseed, now.yseed,
pch = plot.params$pch.seeds, cex = plot.params$cex.seeds,
col = plot.params$col.seeds, lwd = 3
)
}
list(colors = eems.colors, levels = eems.levels)
}
#' A function to plot raw Voronoi diagrams of effective migration and diversity rates
#'
#' Given a set of EEMS output directories, this function takes random draws from the posterior
#' distribution of the migration and diversity rate parameters. Each draw is visualized as two
#' raw Voronoi diagrams; the migration diagram is saved to a file ending in \code{mvoronoiXX},
#' the diversity diagram is saved to a file ending in \code{qvoronoiXX} where \code{XX} is
#' a numeric id. Specify the number of times to draw from the posterior with the argument
#' \code{post.draws}. If \code{post.draws = 10}, then \code{eems.voronoi.samples} will generate
#' plots with id \code{XX = 1} to \code{XX = 10}.
#' This function differs from [eems.posterior.draws()] by displaying raw, unsmoothed Voronoi diagrams.
#'
#' Note about the implementation: \code{eems.voronoi.samples} samples randomly from the posterior
#' draws saved during the execution of EEMS, after burn-in and thinning.
#' @param post.draws Number of times to sample from the posterior. The default is 1.
#' @param add.seeds A logical value indicating whether to add the Voronoi seeds or not.
#' @param col.seeds The color of the Voronoi seeds. Defaults to \code{green}.
#' @param pch.seeds The symbol, specified as an integer, or the character to be used for
#' plotting the Voronoi seeds. Defaults to 4.
#' @param cex.seeds The size of the symbol/character used for plotting the Voronoi seeds.
#' Defaults to 1.
#' @param cex.demes The size of the symbol/character used for plotting observed demes.
#' Defaults to 1.
#' @param out.png A logical value which, if set, forces output graphics to be generated as PNGs
#' (if `TRUE`) or PDFs (if `FALSE`). Defaults to `FALSE`.
#' @inheritParams eems.plots
#' @returns None
#' @references Light A and Bartlein PJ (2004). The End of the Rainbow? Color Schemes for
#' Improved Data Graphics. EOS Transactions of the American Geophysical Union, 85(40), 385.
#' @examples
#' # Use the provided example or supply the path to your own EEMS run.
#' extdata_path <- system.file("extdata", package = "reems")
#' eems_results <- file.path(extdata_path, "EEMS-example")
#' # Create a temporary output directory for this example
#' outdir <- file.path(tempdir(), "path_out")
#' dir.create(outdir, showWarnings = FALSE)
#' name_figures <- file.path(outdir, "eemsplot_out")
#'
#' # Plot a series of Voronoi diagrams for the EEMS model parameters:
#' # the effective migration rates (m) and the effective diversity rates (q).
#' eems.voronoi.samples(
#' mcmcpath = eems_results,
#' plotpath = paste0(name_figures, "-voronoi-diagrams"),
#' longlat = TRUE,
#' post.draws = 2,
#' out.png = FALSE
#' )
#' # Delete the output directory to tidy up.
#' unlink(outdir, recursive = TRUE, force = TRUE)
#' @seealso \code{\link{eems.posterior.draws}}
#' @export
eems.voronoi.samples <- function(mcmcpath,
plotpath,
longlat,
post.draws = 1,
plot.width = 10,
plot.height = 10,
out.png = FALSE,
res = 600,
add.grid = FALSE,
col.grid = "gray80",
lwd.grid = 1,
add.outline = TRUE,
col.outline = "gray80",
lwd.outline = 2,
add.demes = FALSE,
col.demes = "gray80",
pch.demes = 19,
cex.demes = 1,
add.seeds = TRUE,
col.seeds = "#8AE234",
pch.seeds = 4,
cex.seeds = 1,
eems.colors = NULL,
m.colscale = NULL,
q.colscale = NULL,
add.title = FALSE) {
load.required.package(package = "deldir", required.by = "eems.voronoi.samples")
plot.params <- list(
eems.colors = eems.colors, m.colscale = m.colscale, q.colscale = q.colscale,
add.grid = add.grid, add.outline = add.outline, add.demes = add.demes, add.seeds = add.seeds,
col.grid = col.grid, col.outline = col.outline, col.demes = col.demes, col.seeds = col.seeds,
lwd.grid = lwd.grid, lwd.outline = lwd.outline, pch.demes = pch.demes, pch.seeds = pch.seeds,
cex.seeds = cex.seeds, min.cex.demes = cex.demes, max.cex.demes = cex.demes,
add.title = add.title
)
plot.params <- check.plot.params(plot.params)
# A vector of EEMS output directories, for the same dataset.
# Assume that if eemsrun.txt exists, then all EEMS output files exist.
mcmcpath <- mcmcpath[file.exists(file.path(mcmcpath, "eemsrun.txt"))]
if (!length(mcmcpath)) {
stop("Please provide at least one existing EEMS output directory, mcmcpath")
}
dimns <- read.dimns(mcmcpath, longlat)
save.params <- list(height = plot.height, width = plot.width, res = res, out.png = out.png)
message("Processing the following EEMS output directory :")
message(mcmcpath)
plot.params$add.grid <- add.grid
plot.params$all.demes <- FALSE
plot.params$add.demes <- FALSE
plot_with_graphics_device(
paste0(plotpath, "-mvoronoi"),
save.params,
for (draw in seq(post.draws)) {
# Choose one output directory at random
voronoi.diagram(sample(mcmcpath, 1),
dimns, longlat, plot.params,
post.draws = post.draws, is.mrates = TRUE
)
},
par.args = list(las = 1, font.main = 1, mar = c(0, 0, 0, 0) + 0.1)
)
plot.params$add.grid <- FALSE
plot.params$all.demes <- add.demes
plot_with_graphics_device(
paste0(plotpath, "-qvoronoi"),
save.params,
for (draw in seq(post.draws)) {
# Choose one output directory at random
voronoi.diagram(sample(mcmcpath, 1),
dimns, longlat, plot.params,
post.draws = post.draws, is.mrates = FALSE
)
},
par.args = list(las = 1, font.main = 1)
)
invisible(NULL)
}
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