Newer
Older
#'Plot Maps of Most Likely Quantiles
#'
#'@author Veronica Torralba, \email{veronica.torralba@bsc.es}, Nicolau Manubens, \email{nicolau.manubens@bsc.es}
#'@description This function receives as main input (via the parameter \code{probs}) a collection of longitude-latitude maps, each containing the probabilities (from 0 to 1) of the different grid cells of belonging to a category. As many categories as maps provided as inputs are understood to exist. The maps of probabilities must be provided on a common rectangular regular grid, and a vector with the longitudes and a vector with the latitudes of the grid must be provided. The input maps can be provided in two forms, either as a list of multiple two-dimensional arrays (one for each category) or as a three-dimensional array, where one of the dimensions corresponds to the different categories.
#'
#'@param probs a list of bi-dimensional arrays with the named dimensions 'latitude' (or 'lat') and 'longitude' (or 'lon'), with equal size and in the same order, or a single tri-dimensional array with an additional dimension (e.g. 'bin') for the different categories. The arrays must contain probability values between 0 and 1, and the probabilities for all categories of a grid cell should not exceed 1 when added.
#'@param lon a numeric vector with the longitudes of the map grid, in the same order as the values along the corresponding dimension in \code{probs}.
#'@param lat a numeric vector with the latitudes of the map grid, in the same order as the values along the corresponding dimension in \code{probs}.
#'@param cat_dim the name of the dimension along which the different categories are stored in \code{probs}. This only applies if \code{probs} is provided in the form of 3-dimensional array. The default expected name is 'bin'.
#'@param bar_titles vector of character strings with the names to be drawn on top of the color bar for each of the categories. As many titles as categories provided in \code{probs} must be provided.
#'@param col_unknown_cat character string with a colour representation of the colour to be used to paint the cells for which no category can be clearly assigned. Takes the value 'white' by default.
#'@param ... additional parameters to be sent to \code{PlotCombinedMap} and \code{PlotEquiMap}.
#'@seealso \code{PlotCombinedMap} and \code{PlotEquiMap}
#'
#'@import s2dverification
#'@importFrom maps map
#'@importFrom graphics box image layout mtext par plot.new
#'@importFrom grDevices adjustcolor bmp colorRampPalette dev.cur dev.new dev.off hcl jpeg pdf png postscript svg tiff
#'@examples
#'x <- array(1:(20 * 10), dim = c(lat = 10, lon = 20)) / 200
#'a <- x * 0.6
#'b <- (1 - x) * 0.6
#'c <- 1 - (a + b)
#'lons <- seq(0, 359.5, length = 20)
#'lats <- seq(-89.5, 89.5, length = 10)
#'PlotMostLikelyQuantileMap(list(a, b, c), lons, lats,
#' toptitle = 'Most likely tercile map',
#' bar_titles = paste('% of belonging to', c('a', 'b', 'c')),
#' brks = 20, width = 10, height = 8)
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
#'
#'# More complex example
#'n_lons <- 40
#'n_lats <- 20
#'n_timesteps <- 100
#'n_bins <- 4
#'
#'# 1. Generation of sample data
#'lons <- seq(0, 359.5, length = n_lons)
#'lats <- seq(-89.5, 89.5, length = n_lats)
#'
#'# This function builds a 3-D gaussian at a specified point in the map.
#'make_gaussian <- function(lon, sd_lon, lat, sd_lat) {
#' w <- outer(lons, lats, function(x, y) dnorm(x, lon, sd_lon) * dnorm(y, lat, sd_lat))
#' min_w <- min(w)
#' w <- w - min_w
#' w <- w / max(w)
#' w <- t(w)
#' names(dim(w)) <- c('lat', 'lon')
#' w
#'}
#'
#'# This function generates random time series (with values ranging 1 to 5)
#'# according to 2 input weights.
#'gen_data <- function(w1, w2, n) {
#' r <- sample(1:5, n,
#' prob = c(.05, .9 * w1, .05, .05, .9 * w2),
#' replace = TRUE)
#' r <- r + runif(n, -0.5, 0.5)
#' dim(r) <- c(time = n)
#' r
#'}
#'
#'# We build two 3-D gaussians.
#'w1 <- make_gaussian(120, 80, 20, 30)
#'w2 <- make_gaussian(260, 60, -10, 40)
#'
#'# We generate sample data (with dimensions time, lat, lon) according
#'# to the generated gaussians
#'sample_data <- multiApply::Apply(list(w1, w2), NULL,
#' gen_data, n = n_timesteps)$output1
#'
#'# 2. Binning sample data
#'prob_thresholds <- 1:n_bins / n_bins
#'prob_thresholds <- prob_thresholds[1:(n_bins - 1)]
#'thresholds <- quantile(sample_data, prob_thresholds)
#'
#'binning <- function(x, thresholds) {
#' n_samples <- length(x)
#' n_bins <- length(thresholds) + 1
#'
#' thresholds <- c(thresholds, max(x))
#' result <- 1:n_bins
#' lower_threshold <- min(x) - 1
#' for (i in 1:n_bins) {
#' result[i] <- sum(x > lower_threshold & x <= thresholds[i]) / n_samples
#' lower_threshold <- thresholds[i]
#' }
#'
#' dim(result) <- c(bin = n_bins)
#' result
#'}
#'
#'bins <- multiApply::Apply(sample_data, 'time', binning, thresholds)$output1
#'
#'# 3. Plotting most likely quantile/bin
#'PlotMostLikelyQuantileMap(bins, lons, lats,
#' toptitle = 'Most likely quantile map',
#' bar_titles = paste('% of belonging to', letters[1:n_bins]),
#' mask = 1 - (w1 + w2 / max(c(w1, w2))),
#' brks = 20, width = 10, height = 8)
#'
#'@export
PlotMostLikelyQuantileMap <- function(probs, lon, lat, cat_dim = 'bin',
bar_titles = NULL,
col_unknown_cat = 'white',
...) {
# Check probs
error <- FALSE
if (is.list(probs)) {
if (length(probs) < 1) {
stop("Parameter 'probs' must be of length >= 1 if provided as a list.")
}
check_fun <- function(x) {
is.numeric(x) && (length(dim(x)) == 2)
}
if (!all(sapply(probs, check_fun))) {
error <- TRUE
}
ref_dims <- dim(probs[[1]])
equal_dims <- all(sapply(probs, function(x) identical(dim(x), ref_dims)))
if (!equal_dims) {
stop("All arrays in parameter 'probs' must have the same dimension ",
"sizes and names when 'probs' is provided as a list of arrays.")
}
num_probs <- length(probs)
probs <- unlist(probs)
dim(probs) <- c(ref_dims, map = num_probs)
cat_dim <- 'map'
}
if (!is.numeric(probs)) {
error <- TRUE
}
if (is.null(dim(probs))) {
error <- TRUE
}
if (length(dim(probs)) != 3) {
error <- TRUE
}
if (error) {
stop("Parameter 'probs' must be either a numeric array with 3 dimensions ",
" or a list of numeric arrays of the same size with the 'lon' and ",
"'lat' dimensions.")
}
dimnames <- names(dim(probs))
# Check cat_dim
if (is.character(cat_dim)) {
if (is.null(dimnames)) {
stop("Specified a dimension name in 'cat_dim' but no dimension names provided ",
"in 'probs'.")
}
cat_dim <- which(dimnames == cat_dim)
if (length(cat_dim) < 1) {
stop("Dimension 'cat_dim' not found in 'probs'.")
} else if (!is.numeric(cat_dim)) {
stop("Parameter 'cat_dim' must be either a numeric value or a ",
"dimension name.")
}
if (length(cat_dim) != 1) {
stop("Parameter 'cat_dim' must be of length 1.")
}
cat_dim <- round(cat_dim)
nprobs <- dim(probs)[cat_dim]
# Check bar_titles
if (is.null(bar_titles)) {
if (nprobs == 3) {
bar_titles <- list("Below normal (%)", "Normal (%)", "Above normal (%)")
} else if (nprobs == 5) {
bar_titles <- list("Low (%)", "Below normal (%)",
"Normal (%)", "Above normal (%)", "High (%)")
} else {
bar_titles <- paste0("Cat. ", 1:nprobs, " (%)")
}
}
minimum_value <- ceiling(1 / nprobs * 10 * 1.1) * 10
# By now, the PlotCombinedMap function is included below in this file.
# In the future, PlotCombinedMap will be part of s2dverification and will
# be properly imported.
PlotCombinedMap(probs * 100, lon, lat, map_select_fun = max,
display_range = c(minimum_value, 100),
map_dim = cat_dim,
bar_titles = bar_titles,
col_unknown_map = col_unknown_cat, ...)
}
PlotCombinedMap <- function(maps, lon, lat,
map_select_fun, display_range,
map_dim = 'map',
brks = NULL, cols = NULL,
col_unknown_map = 'white',
mask = NULL, col_mask = 'grey',
bar_titles = NULL, legend_scale = 1,
fileout = NULL, width = 8, height = 5,
size_units = 'in', res = 100,
...) {
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
# If there is any filenames to store the graphics, process them
# to select the right device
if (!is.null(fileout)) {
deviceInfo <- .SelectDevice(fileout = fileout, width = width, height = height,
units = size_units, res = res)
saveToFile <- deviceInfo$fun
fileout <- deviceInfo$files
}
# Check probs
error <- FALSE
if (is.list(maps)) {
if (length(maps) < 1) {
stop("Parameter 'maps' must be of length >= 1 if provided as a list.")
}
check_fun <- function(x) {
is.numeric(x) && (length(dim(x)) == 2)
}
if (!all(sapply(maps, check_fun))) {
error <- TRUE
}
ref_dims <- dim(maps[[1]])
equal_dims <- all(sapply(maps, function(x) identical(dim(x), ref_dims)))
if (!equal_dims) {
stop("All arrays in parameter 'maps' must have the same dimension ",
"sizes and names when 'maps' is provided as a list of arrays.")
}
num_maps <- length(maps)
maps <- unlist(maps)
dim(maps) <- c(ref_dims, map = num_maps)
map_dim <- 'map'
}
if (!is.numeric(maps)) {
error <- TRUE
}
if (is.null(dim(maps))) {
error <- TRUE
}
if (length(dim(maps)) != 3) {
error <- TRUE
}
if (error) {
stop("Parameter 'maps' must be either a numeric array with 3 dimensions ",
" or a list of numeric arrays of the same size with the 'lon' and ",
"'lat' dimensions.")
}
dimnames <- names(dim(maps))
# Check map_dim
if (is.character(map_dim)) {
if (is.null(dimnames)) {
stop("Specified a dimension name in 'map_dim' but no dimension names provided ",
"in 'maps'.")
}
map_dim <- which(dimnames == map_dim)
if (length(map_dim) < 1) {
stop("Dimension 'map_dim' not found in 'maps'.")
} else {
map_dim <- map_dim[1]
}
} else if (!is.numeric(map_dim)) {
stop("Parameter 'map_dim' must be either a numeric value or a ",
"dimension name.")
}
if (length(map_dim) != 1) {
stop("Parameter 'map_dim' must be of length 1.")
}
map_dim <- round(map_dim)
# Work out lon_dim and lat_dim
lon_dim <- NULL
if (!is.null(dimnames)) {
lon_dim <- which(dimnames %in% c('lon', 'longitude'))[1]
}
if (length(lon_dim) < 1) {
lon_dim <- (1:3)[-map_dim][1]
}
lon_dim <- round(lon_dim)
lat_dim <- NULL
if (!is.null(dimnames)) {
lat_dim <- which(dimnames %in% c('lat', 'latitude'))[1]
}
if (length(lat_dim) < 1) {
lat_dim <- (1:3)[-map_dim][2]
}
lat_dim <- round(lat_dim)
# Check lon
if (!is.numeric(lon)) {
stop("Parameter 'lon' must be a numeric vector.")
}
if (length(lon) != dim(maps)[lon_dim]) {
stop("Parameter 'lon' does not match the longitude dimension in 'maps'.")
# Check lat
if (!is.numeric(lat)) {
stop("Parameter 'lat' must be a numeric vector.")
}
if (length(lat) != dim(maps)[lat_dim]) {
stop("Parameter 'lat' does not match the longitude dimension in 'maps'.")
# Check map_select_fun
if (is.numeric(map_select_fun)) {
if (length(dim(map_select_fun)) != 2) {
stop("Parameter 'map_select_fun' must be an array with dimensions ",
"'lon' and 'lat' if provided as an array.")
}
if (!identical(dim(map_select_fun), dim(maps)[-map_dim])) {
stop("The dimensions 'lon' and 'lat' in the 'map_select_fun' array must ",
"have the same size, name and order as in the 'maps' parameter.")
}
}
if (!is.function(map_select_fun)) {
stop("The parameter 'map_select_fun' must be a function or a numeric array.")
}
# Check display_range
if (!is.numeric(display_range) || length(display_range) != 2) {
stop("Parameter 'display_range' must be a numeric vector of length 2.")
}
# Check brks
if (is.null(brks) || (is.numeric(brks) && length(brks) == 1)) {
num_brks <- 5
if (is.numeric(brks)) {
num_brks <- brks
}
brks <- seq(from = display_range[1], to = display_range[2], length.out = num_brks)
}
if (!is.numeric(brks)) {
stop("Parameter 'brks' must be a numeric vector.")
}
# Check cols
col_sets <- list(c("#A1D99B", "#74C476", "#41AB5D", "#238B45"),
c("#6BAED6FF", "#4292C6FF", "#2171B5FF", "#08519CFF"),
c("#FFEDA0FF", "#FED976FF", "#FEB24CFF", "#FD8D3CFF"),
c("#FC4E2AFF", "#E31A1CFF", "#BD0026FF", "#800026FF"),
c("#FCC5C0", "#FA9FB5", "#F768A1", "#DD3497"))
if (is.null(cols)) {
if (length(col_sets) >= dim(maps)[map_dim]) {
chosen_sets <- 1:(dim(maps)[map_dim])
chosen_sets <- chosen_sets + floor((length(col_sets) - length(chosen_sets)) / 2)
} else {
chosen_sets <- array(1:length(col_sets), dim(maps)[map_dim])
}
cols <- col_sets[chosen_sets]
} else {
if (!is.list(cols)) {
stop("Parameter 'cols' must be a list of character vectors.")
}
if (!all(sapply(cols, is.character))) {
stop("Parameter 'cols' must be a list of character vectors.")
}
if (length(cols) != dim(maps)[map_dim]) {
stop("Parameter 'cols' must be a list of the same length as the number of ",
"maps in 'maps'.")
}
}
for (i in 1:length(cols)) {
if (length(cols[[i]]) != (length(brks) - 1)) {
cols[[i]] <- colorRampPalette(cols[[i]])(length(brks) - 1)
}
}
# Check bar_titles
if (is.null(bar_titles)) {
if (!is.null(names(cols))) {
bar_titles <- names(cols)
} else {
bar_titles <- paste0("Map ", 1:length(cols))
}
} else {
if (!is.character(bar_titles)) {
stop("Parameter 'bar_titles' must be a character vector.")
}
if (length(bar_titles) != length(cols)) {
stop("Parameter 'bar_titles' must be of the same length as the number of ",
"maps in 'maps'.")
# Check legend_scale
if (!is.numeric(legend_scale)) {
stop("Parameter 'legend_scale' must be numeric.")
}
# Check col_unknown_map
if (!is.character(col_unknown_map)) {
stop("Parameter 'col_unknown_map' must be a character string.")
}
# Check col_mask
if (!is.character(col_mask)) {
stop("Parameter 'col_mask' must be a character string.")
}
# Check mask
if (!is.null(mask)) {
if (!is.numeric(mask)) {
stop("Parameter 'mask' must be numeric.")
}
if (length(dim(mask)) != 2) {
stop("Parameter 'mask' must have two dimensions.")
}
if ((dim(mask)[1] != dim(maps)[lat_dim]) ||
(dim(mask)[2] != dim(maps)[lon_dim])) {
stop("Parameter 'mask' must have dimensions c(lat, lon).")
}
#----------------------
# Identify the most likely map
#----------------------
if (is.function(map_select_fun)) {
range_width <- display_range[2] - display_range[1]
ml_map <- apply(maps, c(lat_dim, lon_dim), function(x) {
if (any(is.na(x))) {
res <- NA
} else {
res <- which(x == map_select_fun(x))
if (length(res) > 0) {
res <- res[1]
if (map_select_fun(x) < display_range[1] || map_select_fun(x) > display_range[2]) {
res <- -0.5
} else {
res <- res + (map_select_fun(x) - display_range[1]) / range_width
}
} else {
res <- -0.5
}
}
res
})
} else {
stop("Providing 'map_select_fun' as array not implemented yet.")
ml_map <- map_select_fun
nmap <- dim(maps)[map_dim]
nlat <- length(lat)
nlon <- length(lon)
#----------------------
# Set latitudes from minimum to maximum
#----------------------
if (lat[1] > lat[nlat]){
lat <- lat[nlat:1]
indices <- list(nlat:1, TRUE)
ml_map <- do.call("[", c(list(x = ml_map), indices))
if (!is.null(mask)){
mask <- mask[nlat:1, ]
}
}
#----------------------
# Set layout and parameters
#----------------------
# Open connection to graphical device
if (!is.null(fileout)) {
saveToFile(fileout)
} else if (names(dev.cur()) == 'null device') {
dev.new(units = size_units, res = res, width = width, height = height)
}
plot.new()
par(font.main = 1)
layout(matrix(c(rep(1, nmap),2:(nmap + 1)), 2, nmap, byrow = TRUE), heights = c(6, 1.5))
#----------------------
# Set colors and breaks and then PlotEquiMap
#----------------------
tcols <- c(col_unknown_map, cols[[1]])
for (k in 2:nmap) {
tcols <- append(tcols, c(col_unknown_map, cols[[k]]))
brks_norm <- seq(0, 1, length.out = length(brks))
tbrks <- c(-1, brks_norm + rep(1:nmap, each = length(brks)))
PlotEquiMap(var = ml_map, lon = lon, lat = lat,
brks = tbrks, cols = tcols, drawleg = FALSE,
filled.continents = FALSE, ...)
#----------------------
# Add overplot on top
#----------------------
if (!is.null(mask)) {
cols_mask <- sapply(seq(from = 0, to = 1, length.out = 10),
function(x) adjustcolor(col_mask, alpha.f = x))
image(lon, lat, t(mask), axes = FALSE, col = cols_mask,
breaks = seq(from = 0, to = 1, by = 0.1),
xlab='', ylab='', add = TRUE, xpd = TRUE)
if (!exists('coast_color')) {
coast_color <- 'black'
}
if (min(lon) < 0) {
map('world', interior = FALSE, add = TRUE, lwd = 1, col = coast_color) # Low resolution world map (lon -180 to 180).
} else {
map('world2', interior = FALSE, add = TRUE, lwd = 1, col = coast_color) # Low resolution world map (lon 0 to 360).
}
#----------------------
# Add colorbars
#----------------------
if ('toptitle' %in% names(args)) {
size_title <- 1
if ('title_scale' %in% names(args)) {
size_title <- args[['title_scale']]
}
old_mar <- par('mar')
old_mar[3] <- old_mar[3] - (2 * size_title + 1)
par(mar = old_mar)
}
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
for (k in 1:nmap){
ColorBar(brks = brks, cols = cols[[k]], vertical = FALSE,
draw_separators = TRUE, extra_margin = c(2, 0, 2, 0),
label_scale = legend_scale * 1.5)
if (!is.null(bar_titles)) {
mtext(bar_titles[[k]], 3, line = -3, cex = 1.5)
}
}
# If the graphic was saved to file, close the connection with the device
if (!is.null(fileout)) dev.off()
}
# Once PlotCombined is included in s2dverification and removed from
# CSTools, this function will be removed from CSTools too.
.SelectDevice <- function(fileout, width, height, units, res) {
# This function is used in the plot functions to check the extension of the
# files where the graphics will be stored and select the right R device to
# save them.
# If the vector of filenames ('fileout') has files with different
# extensions, then it will only accept the first one, changing all the rest
# of the filenames to use that extension.
# We extract the extension of the filenames: '.png', '.pdf', ...
ext <- regmatches(fileout, regexpr("\\.[a-zA-Z0-9]*$", fileout))
if (length(ext) != 0) {
# If there is an extension specified, select the correct device
## units of width and height set to accept inches
if (ext[1] == ".png") {
saveToFile <- function(fileout) {
png(filename = fileout, width = width, height = height, res = res, units = units)
}
} else if (ext[1] == ".jpeg") {
saveToFile <- function(fileout) {
jpeg(filename = fileout, width = width, height = height, res = res, units = units)
}
} else if (ext[1] %in% c(".eps", ".ps")) {
saveToFile <- function(fileout) {
postscript(file = fileout, width = width, height = height)
}
} else if (ext[1] == ".pdf") {
saveToFile <- function(fileout) {
pdf(file = fileout, width = width, height = height)
}
} else if (ext[1] == ".svg") {
saveToFile <- function(fileout) {
svg(filename = fileout, width = width, height = height)
}
} else if (ext[1] == ".bmp") {
saveToFile <- function(fileout) {
bmp(filename = fileout, width = width, height = height, res = res, units = units)
}
} else if (ext[1] == ".tiff") {
saveToFile <- function(fileout) {
tiff(filename = fileout, width = width, height = height, res = res, units = units)
}
} else {
warning("file extension not supported, it will be used '.eps' by default.")
## In case there is only one filename
fileout[1] <- sub("\\.[a-zA-Z0-9]*$", ".eps", fileout[1])
ext[1] <- ".eps"
saveToFile <- function(fileout) {
postscript(file = fileout, width = width, height = height)
}
}
# Change filenames when necessary
if (any(ext != ext[1])) {
warning(paste0("some extensions of the filenames provided in 'fileout' are not ", ext[1],". The extensions are being converted to ", ext[1], "."))
fileout <- sub("\\.[a-zA-Z0-9]*$", ext[1], fileout)
}
} else {
# Default filenames when there is no specification
warning("there are no extensions specified in the filenames, default to '.eps'")
fileout <- paste0(fileout, ".eps")
saveToFile <- postscript
}
# return the correct function with the graphical device, and the correct
# filenames
list(fun = saveToFile, files = fileout)