Newer
Older
#'Plot map in Robinson or other projections
#'
#'Transform a regular grid longitude-latitude data to a different projection and
#'plot the map. The target projection must be a valid CRS string, preferrably be
#'EPSG or ESRI code; check \link[sf]{st_crs} for more explanation. This function
#'is mainly tested for Robinson projection (ESRI:54030), but it can work with
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
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
#'The map can be plotted by points or polygon. A legend can be plotted as either
#'a color bar or a discrete ggplot legend. Dots can be drawn on top of the data,
#'which can be used for significance test. A mask can be added to not plot the
#'data specified. A number of options is provided to adjust aesthetics, like
#'position, size, colors, etc.
#'
#'@param data A numeric array with longitude and latitude dimensions. The grid
#' should be regular grid. It can contain NA values.
#'@param lon A numeric vector of longitude locations of the cell centers of the
#' grid of 'data'. Expected to be regularly spaced, within the range of either
#' [-180, 180] or [0, 360].
#'@param lat A numeric vector of latitude locations of the cell centers of the
#' grid of 'data'. Expected to be regularly spaced, within the range [-90, 90]
#' of ascending or descending order.
#'@param lon_dim A character string indicating the longitude dimension name in
#' 'data'. If it is NULL, the function tries to find the name in
#' \code{s2dv:::.KnownLonNames}. The default value is NULL.
#'@param lat_dim A character string indicating the latitude dimension name in
#' 'data'. If it is NULL, the function tries to find the name in
#' \code{s2dv:::.KnownLatNames}. The default value is NULL.
#'@param target_proj A character string indicating the target projection. It
#' should be a valid crs string. The default projection is Robinson
#' (ESRI:54030). Note that the character string may work differently depending
#' on PROJ and GDAL module version.
#'@param legend A character string indicating the legend style. It can be 's2dv'
#' (color bar by \code{ColorBarContinuous()}), 'ggplot2' (discrete legend by
#' ggplot2), or NULL (no legend),
#'@param style A character string indicating the plotting style. It can be
#' 'point' or 'polygon'. The default value is 'point'. Note that 'polygon' may
#' be time- and memory-consuming for global or high-resolution data.
#'@param dots An array with the same dimensions as 'data' of [0, 1] or logical
#' indicating the grids to plot dots. The value 0 or FALSE is the point to be
#' dotted.
#'@param mask An array with the same dimensions as 'data' of [0, 1] or logical
#' indicating the grids to not plot data. The value 0 or FALSE is the point not
#' to be plotted.
#'@param brks,cols,bar_limits,triangle_ends Usually only providing 'brks' is
#' enough to generate the desired color bar. These parameters allow to
#' define n breaks that define n - 1 intervals to classify each of the values
#' in 'data'. The corresponding grid cell of a given value in 'data' will be
#' colored in function of the interval it belongs to. These parameters are
#' sent to \code{ColorBarContinuous()} to generate the breaks and colours.
#' Additional colors for values beyond the limits of the colour bar are also
#' generated and applied to the plot if 'bar_limits' or 'brks' and
#' 'triangle_ends' are properly provided to do so. See ?ColorBarContinuous for
#' a full explanation.
#'@param col_inf,col_sup,colNA Colour identifiers to color the values that
#' excess the extremes of the color bar and to color NAs, respectively. 'colNA'
#' takes attr(cols, 'na_color') if available by default, where cols is the
#' parameter 'cols' if provided or the vector of colors returned by
#' 'color_fun'. 'col_inf' and 'col_sup' will take the value of 'colNA' if not
#' specified. See ?ColorBarContinuous for a full explanation.
#'@param color_fun,bar_extra_margin Set of
#' parameters to control the visual aspect of the drawn colour bar
#' (1/3). See ?ColorBarContinuous for a full explanation.
#'@param vertical A logical value indicating the direction of colorbar if
#' parameter 'legend' is 's2dv'. The default value is TRUE.
#'@param toptitle A character string of the top title of the figure, scalable
#' with parameter 'title_size'.
#'@param caption A character string of the caption located at left-bottom of the
#' plot.
#'@param units A character string of the data units, which is the title of the
#' legend.
#'@param crop_coastlines A named numeric vector [lonmin, lonmax, latmin, latmax]
#' indicating the region to plot coastlines. Note that the longitude range
#' cannot exceed 180 degrees.
#'@param point_size A number of the size of the data points if "style = 'point'".
#' The default is 'auto' and the function tries to find the appropriate size.
#'@param title_size A number of the size of the top title. The default is 16.
#'@param dots_size A number of the size of the dots. The default is 0.5.
#'@param dots_shape A number indicating the dot shape recognized by parameter
#' 'shape' in \code{geom_point()}.
#'@param coastlines_width A number indicating the width of the coastlines.
#'@param fileout A character string of the path to save the plot. If not
#' specified (default), a graphic device will pop up. The extension should be
#' accepted by \code{ggsave()}.
#'@param width A number of the plot width, in the units specified in parameter
#' 'size_units'. The default is 8.
#'@param height A number of the plot height, in the units specified in parameter
#' 'size_units'. The default is 4.
#'@param size_units A character string of the units of the size of the device
#' (file or window) to plot in. The default is 'in' (inches). See ?ggsave and
#' ?Devices for details of the corresponding device.
#'@param res Resolution of the device (file or window) to plot in. The default
#' value is 300. See ?ggsave 'dpi' and ?Devices for details of the
#' corresponding device.
#'
#'@return A map plot with speficied projection, either in pop-up window or a
#' saved file.
#'
#'@examples
#'data <- array(rep(seq(-10, 10, length.out = 181), 360) + rnorm(360),
#' dim = c(lat = 181, lon = 360))
#'dots <- data
#'dots[which(dots < 4 & dots > -4)] <- 0
#'dots[which(dots != 0)] <- 1
#'VizRobinson(data, lon = 0:359, lat = -90:90, dots = dots,
#' brks = seq(-10, 10, length.out = 11),
#' caption = 'Robinson Projection',
#' bar_extra_margin = c(0, 1, 0, 1), width = 8, height = 6)
#'VizRobinson(data, lon = 0:359, lat = -90:90, mask = dots, legend = 'ggplot2',
#' target_proj = "+proj=moll", brks = seq(-10, 10, length.out = 11),
#' color_fun = ClimPalette("purpleorange"), colNA = 'green',
#' toptitle = 'synthetic example', caption = 'Mollweide Projection',
#' width = 8, height = 6)
#'@import sf ggplot2 rnaturalearth cowplot utils
#'@importFrom dplyr mutate group_by summarise
#'@importFrom ClimProjDiags Subset
VizRobinson <- function(data, lon, lat, lon_dim = NULL, lat_dim = NULL,
target_proj = 54030, legend = 's2dv', style = 'point',
dots = NULL, mask = NULL, brks = NULL, cols = NULL, bar_limits = NULL,
triangle_ends = NULL, col_inf = NULL, col_sup = NULL, colNA = NULL,
color_fun = ClimPalette(), bar_extra_margin = rep(0, 4), vertical = TRUE,
toptitle = NULL, caption = NULL, units = NULL, crop_coastlines = NULL,
point_size = "auto", title_size = 16, dots_size = 0.5,
dots_shape = 47, coastlines_width = 0.3,
fileout = NULL, width = 8, height = 4, size_units = "in",
res = 300) {
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
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
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
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
# Sanity check
# data
data <- drop(data)
if (length(dim(data)) != 2) {
stop("Parameter 'data' must have two dimensions.")
}
dims <- dim(data)
# lon, lon_dim
if (is.null(lon_dim)) {
lon_dim <- names(dims)[names(dims) %in% .KnownLonNames()]
if (identical(lon_dim, character(0))) {
stop("Cannot find known longitude name in data dimension. Please define parameter 'lon_dim'.")
}
}
if (is.unsorted(lon)) {
warning("Parameter 'lon' should be sorted to guarantee the correct result.")
}
# lat, lat_dim
if (is.null(lat_dim)) {
lat_dim <- names(dims)[names(dims) %in% .KnownLatNames()]
if (identical(lat_dim, character(0))) {
stop("Cannot find known latitude name in data dimension. Please define parameter 'lat_dim'.")
}
}
if (!all(names(dims) %in% c(lat_dim, lon_dim))) {
stop("Dimensions names in paramter 'data' should match 'lat_dim' and 'lon_dim.")
}
if (length(lon) != dims[lon_dim]) {
stop("Length of parameter 'lon' should match longitude dimension in 'data'.")
}
if (length(lat) != dims[lat_dim]) {
stop("Length of parameter 'lat' should match latitude dimension in 'data'.")
}
# Reorder data
data <- aperm(data, match(names(dim(data)), c(lon_dim, lat_dim)))
# Make lat always from 90 to -90
sort_lat <- FALSE
if (!is.unsorted(lat)) {
lat <- rev(lat)
data <- ClimProjDiags::Subset(data, along = lat_dim, indices = seq(length(lat), 1, -1))
sort_lat <- TRUE
}
# original_proj: it can only be regular grid now
original_proj <- st_crs(4326)
# tartget_proj
if (is.null(target_proj)) {
stop("Parameter 'target_proj' cannot be NULL.")
} else {
target_proj_tmp <- st_crs(target_proj)
if (is.na(target_proj_tmp)) {
warning(paste0("Try ESRI code: ESRI:", target_proj))
target_proj <- st_crs(paste0("ESRI:", target_proj))
} else {
target_proj <- target_proj_tmp
}
}
# legend
if (!is.null(legend) && (!legend %in% c('s2dv', 'ggplot2'))) {
stop("Parameter 'legend' must be NULL, ggplot2 or s2dv.")
}
# style
if (!style %in% c('point', 'polygon') || length(style) != 1) {
stop("Parameter 'style' must be 'point' or 'polygon'.")
}
if (style == 'polygon') {
# polygon is slow for global map (and may be wrong) Confirm if users want to proceed
if ((abs(diff(range(lon))) > 350 & abs(diff(range(lat))) > 175) |
(prod(dim(data)) >= (180 * 360))) {
if (!isTRUE(utils::askYesNo("The region seems to be global and style 'polygon' is chosen. It may be time- and memory-consuming to plot the map. Are you sure that you want to continue?"))) {
return(invisible())
}
}
}
# dots
if (!is.null(dots)) {
dots <- drop(dots)
if (!is.array(dots) || any(!names(dim(dots)) %in% c(lon_dim, lat_dim))) {
stop("Parameter 'dots' must have two dimensions named as longitude and latitude dimensions in 'data'.")
} else {
dots <- aperm(dots, match(names(dim(dots)), c(lon_dim, lat_dim)))
}
if (!identical(dim(dots), dim(data))) {
stop("Parameter 'dots' must have the same dimensions as 'data'.")
} else if (is.numeric(dots)) {
if (all(dots %in% c(0, 1))) {
dots <- array(as.logical(dots), dim = dim(dots))
} else {
stop("Parameter 'dots' must have only TRUE/FALSE or 0/1.")
}
} else if (is.logical(dots)) {
if (!all(dots %in% c(T, F))) {
stop("Parameter 'dots' must have only TRUE/FALSE or 0/1.")
}
} else {
stop("Parameter 'dots' must be a logical or numerical array.")
}
}
# mask
if (!is.null(mask)) {
mask <- drop(mask)
if (!is.array(mask) || any(!names(dim(mask)) %in% c(lon_dim, lat_dim))) {
stop("Parameter 'mask' must have two dimensions named as longitude and latitude dimensions in 'data'.")
} else {
mask <- aperm(mask, match(names(dim(mask)), c(lon_dim, lat_dim)))
}
if (!identical(dim(mask), dim(data))) {
stop("Parameter 'mask' must have the same dimensions as 'data'.")
} else if (is.numeric(mask)) {
if (all(mask %in% c(0, 1))) {
mask <- array(as.logical(mask), dim = dim(mask))
} else {
stop("Parameter 'mask' must have only TRUE/FALSE or 0/1.")
}
} else if (is.logical(mask)) {
if (!all(mask %in% c(T, F))) {
stop("Parameter 'mask' must have only TRUE/FALSE or 0/1.")
}
} else {
stop("Parameter 'mask' must be a logical or numerical array.")
}
}
# Color bar
## Check: brks, cols, bar_limits, color_fun, bar_extra_margin, units
## Build: brks, cols, bar_limits, col_inf, col_sup
var_limits <- c(min(data, na.rm = TRUE), max(data, na.rm = TRUE))
colorbar <- ColorBarContinuous(brks = brks, cols = cols, vertical = vertical, subsampleg = NULL,
bar_limits = bar_limits, var_limits = var_limits, triangle_ends = triangle_ends,
col_inf = col_inf, col_sup = col_sup, color_fun = color_fun,
plot = FALSE, draw_ticks = TRUE, draw_separators = FALSE,
triangle_ends_scale = 1, extra_labels = NULL,
title = units, title_scale = 1, # units_scale
label_scale = 1, tick_scale = 1, #bar_tick_scale
extra_margin = bar_extra_margin, label_digits = 4)
brks <- colorbar$brks
cols <- colorbar$cols
col_inf <- colorbar$col_inf
col_sup <- colorbar$col_sup
bar_limits <- c(head(brks, 1), tail(brks, 1))
# colNA
if (is.null(colNA)) {
if ('na_color' %in% names(attributes(cols))) {
colNA <- attr(cols, 'na_color')
if (!.IsColor(colNA)) {
stop("The 'na_color' provided as attribute of the colour vector must be a valid colour identifier.")
}
} else {
colNA <- 'pink'
}
} else if (!.IsColor(colNA)) {
stop("Parameter 'colNA' must be a valid colour identifier.")
}
# toptitle
if (!is.null(toptitle) && !is.character(toptitle)) {
stop("Parameter 'toptitle' must be a character string.")
}
# caption
if (!is.null(caption) && !is.character(caption)) {
stop("Parameter 'caption' must be a character string.")
}
# crop_coastlines
if (!is.null(crop_coastlines)) {
# if crop_coastlines doesn't have name, [lonmin, lonmax, latmin, latmax]
if (is.null(names(crop_coastlines))) {
names(crop_coastlines) <- c("lonmin", "lonmax", "latmin", "latmax")
} else if (!identical(sort(names(crop_coastlines)), sort(c("latmax", "latmin", "lonmax", "lonmin")))) {
stop("Parameter 'crop_coastlines' needs to have names 'latmax', 'latmin', 'lonmax', 'lonmin'.")
}
}
# point_size
if (point_size == 'auto') {
# 360x181 with default setting, 0.05
point_size <- round(0.05 * (360 * 181) / (length(lon) * length(lat)), 2)
} else if (!is.numeric(point_size)) {
stop("Parameter 'point_size' must be a number.")
}
#
#=================================================================
# Adapt s2dv ColorBar parameters to ggplot plot
# If legend is NULL, still tune with s2dv legend way
if (is.null(legend) || legend == 's2dv') {
# the colorbar triangle color. If it is NULL (no triangle plotted), use colNA
col_inf_image <- ifelse(is.null(col_inf), colNA, col_inf)
col_sup_image <- ifelse(is.null(col_sup), colNA, col_sup)
cols_ggplot <- c(col_inf_image, cols, col_sup_image)
# Add triangles to brks
brks_ggplot <- brks
if (max(data, na.rm = T) > tail(brks, 1)) {
brks_ggplot <- c(brks_ggplot, max(data, na.rm = T))
} else {
brks_ggplot <- c(brks_ggplot, tail(brks, 1) + diff(tail(brks, 2)))
}
if (min(data, na.rm = T) < brks[1]) {
brks_ggplot <- c(min(data, na.rm = T), brks_ggplot)
} else {
brks_ggplot <- c(brks[1] - diff(brks[1:2]), brks_ggplot)
}
} else { # ggplot2 legend
brks_ggplot <- brks
cols_ggplot <- cols
}
# Build data dataframe
lonlat_df <- data.frame(lon = rep(as.vector(lon), length(lat)),
lat = sort(rep(as.vector(lat), length(lon)), decreasing = TRUE))
data_df <- lonlat_df %>%
dplyr::mutate(dat = as.vector(data))
lonlat_df_ori <- NULL
# Remove the points where mask = FALSE
if (!is.null(mask)) {
# Save original lonlat_df to plot with expected region
lonlat_df_ori <- st_as_sf(lonlat_df, coords = c("lon", "lat"), crs = original_proj)
lonlat_df_ori <- st_transform(lonlat_df_ori, crs = target_proj)
lonlat_df_ori <- as.data.frame(st_coordinates(lonlat_df_ori))
names(lonlat_df_ori) <- c('long', 'lat')
if (sort_lat) {
mask <- ClimProjDiags::Subset(mask, along = lat_dim, indices = seq(length(lat), 1, -1))
}
mask_df <- data.frame(lon = rep(as.vector(lon), length(lat)),
lat = sort(rep(as.vector(lat), length(lon)), decreasing = TRUE),
mask = as.vector(mask))
data_df <- data_df[mask_df$mask == TRUE, ]
lonlat_df <- data_df[, 1:2]
}
#NOTE: if target_proj = "ESRI:54030", Nord3v2 has different behavior from hub and ws!!
data_df <- st_as_sf(data_df, coords = c("lon", "lat"), crs = original_proj)
data_df <- st_transform(data_df, crs = target_proj)
data_df <- data_df %>%
dplyr::mutate(long = st_coordinates(data_df)[, 1],
lat = st_coordinates(data_df)[, 2])
# Re-project dots
if (!is.null(dots)) {
if (sort_lat) {
dots <- ClimProjDiags::Subset(dots, along = lat_dim, indices = seq(length(lat), 1, -1))
}
dots_df <- data.frame(lon = rep(as.vector(lon), length(lat)),
lat = sort(rep(as.vector(lat), length(lon)), decreasing = TRUE),
dot = as.vector(dots))
dots_df <- st_as_sf(dots_df, coords = c("lon", "lat"), crs = original_proj)
dots_df <- st_transform(dots_df, crs = target_proj)
dots_df <- dots_df %>%
dplyr::mutate(long = st_coordinates(dots_df)[, 1],
lat = st_coordinates(dots_df)[, 2])
dots_df <- subset(dots_df, dot == FALSE)
}
# coastlines
coastlines <- rnaturalearth::ne_coastline(scale = "medium", returnclass = "sf")
## crop the coastlines to the desired range
if (!is.null(crop_coastlines)) {
suppressWarnings({
coastlines <- st_crop(coastlines,
xmin = as.numeric(crop_coastlines['lonmin']),
xmax = as.numeric(crop_coastlines['lonmax']),
ymin = as.numeric(crop_coastlines['latmin']),
ymax = as.numeric(crop_coastlines['latmax']))
})
}
coastlines <- st_transform(coastlines, crs = target_proj)
if (style == 'polygon') {
# Calculate polygon points from regular lat/lon
#NOTE: The original grid must be regular grid with same space
d_lon <- abs(lon[2] - lon[1]) / 2
d_lat <- abs(lat[2] - lat[1]) / 2
lon_poly <- lat_poly <- rep(NA, 4 * dim(lonlat_df)[1])
for (ii in 1:dim(lonlat_df)[1]) {
lon_poly[(ii*4-3):(ii*4)] <- c(lonlat_df$lon[ii] - d_lon, lonlat_df$lon[ii] + d_lon,
lonlat_df$lon[ii] + d_lon, lonlat_df$lon[ii] - d_lon)
lat_poly[(ii*4-3):(ii*4)] <- c(lonlat_df$lat[ii] - d_lat, lonlat_df$lat[ii] - d_lat,
lonlat_df$lat[ii] + d_lat, lonlat_df$lat[ii] + d_lat)
}
# # To prevent out-of-global lon
# lon_poly[which(lon_poly >= 180)] <- 179.9
# lon_poly[which(lon_poly < -180)] <- -180
# To prevent out-of-global lat
lat_poly[which(lat_poly > 90)] <- 90
lat_poly[which(lat_poly < -90)] <- -90
lonlat_df <- data.frame(lon = lon_poly, lat = lat_poly)
# Transfer lon/lat to projection
proj_lonlat <- st_as_sf(lonlat_df, coords = c("lon", "lat"), crs = original_proj)
#NOTE: if target_proj = "ESRI:54030", on Nord3v2, st_transform has lon and lat swapped!
proj_lonlat <- st_transform(proj_lonlat, crs = target_proj)
lonlat_df_proj <- st_coordinates(proj_lonlat)
# Use id to create groups for each polygon
ids <- factor(paste0("id_", 1:dim(data_df)[1]))
values <- data.frame(id = ids,
value = data_df$dat)
positions <- data.frame(id = rep(ids, each = 4),
x = lonlat_df_proj[, 1],
y = lonlat_df_proj[, 2])
datapoly <- merge(values, positions, by = "id")
datapoly <- st_as_sf(datapoly, coords = c("x", "y"), crs = target_proj)
datapoly <- datapoly %>%
dplyr::group_by(id) %>%
dplyr::summarise() %>% #NOTE: VERY SLOW if plot global
dplyr::mutate(value = values[order(values$id), ]$value) %>%
st_cast("POLYGON") %>%
st_convex_hull() # maintain outer polygen (no bowtie shape)
}
# Plots
if (style == 'polygon') {
res_p <- ggplot(data = data_df) + #NOTE: must be data_df?
geom_sf(data = datapoly,
aes(col = cut(value, breaks = brks_ggplot, include.lowest = T),
fill = cut(value, breaks = brks_ggplot, include.lowest = T)))
} else if (style == 'point') {
res_p <- ggplot(data = data_df) +
geom_point(aes(x = long, y = lat,
col = cut(dat, breaks = brks_ggplot, include.lowest = T)),
#NOTE: These two lines make point size vary with lat
#size = point_size / (data_df$lat / min(data_df$lat))) +
#size = (sort(rep(as.vector(lat), length(lon))) / max(lat)) * point_size) +
size = point_size)
}
if (is.null(lonlat_df_ori)) {
coord_sf_lim <- c(range(data_df$long), range(data_df$lat))
} else {
coord_sf_lim <- c(range(lonlat_df_ori$long), range(lonlat_df_ori$lat))
}
res_p <- res_p +
geom_sf(data = coastlines, colour ='black', size = coastlines_width) +
# Remove background grid and lat/lon label; add white background
theme_void() + theme(plot.background = element_rect(fill = 'white', colour = 'white')) +
# crop the projection
coord_sf(xlim = coord_sf_lim[1:2], ylim = coord_sf_lim[3:4],
expand = TRUE, datum = target_proj)
if (!is.null(dots)) {
res_p <- res_p + geom_point(data = dots_df, aes(x = long, y = lat),
shape = dots_shape, size = dots_size)
#NOTE: This line makes point size vary with lat
#size = dots_size / (dots_df$lat / min(dots_df$lat)))
}
if (identical(legend, 'ggplot2')) {
if (style == 'polygon') {
res_p <- res_p + scale_colour_manual(values = cols_ggplot,
aesthetics = c("colour", "fill"),
drop = FALSE, na.value = colNA) +
guides(fill = guide_legend(title = units, override.aes = list(size = 1)),
color = "none")
} else if (style == 'point') {
res_p <- res_p + scale_colour_manual(values = cols_ggplot,
drop = FALSE, na.value = colNA) +
guides(colour = guide_legend(title = units, override.aes = list(size = 1)))
}
} else { # s2dv or NULL
if (style == 'polygon') {
res_p <- res_p + scale_colour_manual(values = cols_ggplot,
aesthetics = c("colour", "fill"),
drop = FALSE, na.value = colNA)
} else if (style == 'point') {
res_p <- res_p + scale_colour_manual(values = cols_ggplot,
drop = FALSE, na.value = colNA)
}
# Remove ggplot legend
res_p <- res_p + theme(legend.position = "none", plot.margin = margin(0.5, 0, 0, 0, 'cm'))
}
if (!is.null(toptitle)) {
res_p <- res_p + ggtitle(toptitle) +
theme(plot.title = element_text(size = title_size, hjust = 0.5, vjust = 3))
}
if (!is.null(caption)) {
res_p <- res_p + labs(caption = caption) +
theme(plot.caption = element_text(hjust = 0, vjust = 1, margin = margin(0, 0, 0, 0, 'cm')))
}
# s2dv legend fun to put in cowplot::plot_grid
if (identical(legend, 's2dv')) {
fun_legend <- function() {
if (vertical) {
par(mar = c(7.1, 2.2, 7.1, 3.1), mgp = c(3, 1, 0))
} else {
par(mar = c(1.1, 1.2, 0.1, 1.1), mgp = c(3, 1, 0))
}
ColorBarContinuous(brks = brks, cols = cols, vertical = vertical, subsampleg = NULL,
bar_limits = bar_limits, var_limits = var_limits, triangle_ends = triangle_ends,
col_inf = col_inf, col_sup = col_sup, color_fun = color_fun,
plot = TRUE, draw_ticks = TRUE, draw_separators = FALSE,
triangle_ends_scale = 1, extra_labels = NULL,
title = units, title_scale = 1, # units_scale
label_scale = 1, tick_scale = 1, #bar_tick_scale
extra_margin = bar_extra_margin, label_digits = 4)
}
if (vertical) {
res_p <- cowplot::plot_grid(res_p, fun_legend, rel_widths = c(6, 1))
} else {
res_p <- cowplot::plot_grid(res_p, fun_legend, rel_heights = c(5, 1), ncol = 1)
}
res_p <- res_p + theme(plot.background = element_rect(fill = "white", colour = "white"))
}
if (!is.null(fileout)) {
ext <- regmatches(fileout, regexpr("[a-zA-Z0-9]*$", fileout))
ggsave(fileout, res_p, width = width, height = height, dpi = res, units = size_units,
device = ext)
} else { # pop-up window
dev.new(units = size_units, res = res, width = width, height = height)
res_p
}
}