问题
I would like to plot a figure with small multiple maps using ggplot2::geom_sf. The challenge here is how to do this keeping all maps centered in the image and at the same spatial scale. Here is the problem (data for reproducible example below):
A simple map using facet_wrap put all polygons at the same spatial scale, but they are not centered.
ggplot(states6) +
geom_sf() +
facet_wrap(~name_state)
Here is a solution from this SO question
that uses cowplot. In this case, polygons are centered but they come at different spatial scales
g <- purrr::map(unique(states6$name_state),
function(x) {
# subset data
temp_sf <- subset(states6, name_state == x)
ggplot() +
geom_sf(data = temp_sf, fill='black') +
guides(fill = FALSE) +
ggtitle(x) +
ggsn::scalebar(temp_sf, dist = 100, st.size=2,
height=0.01, model = 'WGS84',
transform = T, dist_unit='km')
})
g2 <- cowplot::plot_grid(plotlist = g)
g2
I've found the same problem using the tmaplibrary.
tm_shape(states6) +
tm_borders(col='black') +
tm_fill(col='black') +
tm_facets(by = "name_state ", ncol=3) +
tm_scale_bar(breaks = c(0, 50, 100), text.size = 3)
Desired output
The output I would like to get is something similar to this:
Data for reproducible example
library(sf)
library(geobr)
library(mapview)
library(ggplot2)
library(ggsn)
library(cowplot)
library(purrr)
library(tmap)
# Read all Brazilian states
states <- geobr::read_state(code_state = 'all', year=2015)
# Select six states
states6 <- subset(states, code_state %in% c(35,33,53,29,31,23))
回答1:
It´s not ideal but you can make several plots programmatically with the same box size and then put them together using ::gridExtra. To get the center of each box, use the centroid of each geometry.
library(sf)
library(geobr)
library(mapview)
library(ggplot2)
library(gridExtra)
Read all Brazilian states:
states <- geobr::read_state(code_state = 'all', year=2015)
Select six states:
states6 <- subset(states, code_state %in% c(35,33,53,29,31,23))
centroids, for reference in the ggplot bellow (I had to set the projection, make changes here if needed):
states6$centroid <-
sf::st_transform(states6, 29101) %>%
sf::st_centroid() %>%
sf::st_transform(., '+proj=longlat +ellps=GRS80 +no_defs') %>%
sf::st_geometry()
set padding:
padding <-7
function to make plots:
graph <- function(x){
ggplot2::ggplot(states6[x,]) +
geom_sf() +
coord_sf(xlim = c(states6$centroid[[x]][1]-padding ,
states6$centroid[[x]][1]+padding),
ylim = c(states6$centroid[[x]][2]-padding ,
states6$centroid[[x]][2]+padding),
expand = FALSE)
}
create a bunch of plots:
plot_list <- lapply(X = 1:nrow(states6), FUN = graph)
grid them together:
g <- cowplot::plot_grid(plotlist = plot_list, ncol = 3)
g
回答2:
A bit of a hack, but here is a possible tmap solution based on computing the max width of the different states and then create a "dummy" layer of points spaced max_width/2 from the centroids of each state to "force" a constant width of the facets and thus a constant scale:
library(sf)
library(geobr)
library(tmap)
library(dplyr)
# Read all Brazilian states
states <- geobr::read_state(code_state = 'all', year=2015)
# Select six states
states6 <- subset(states, code_state %in% c(35,33,53,29,31,23)) %>%
sf::st_set_crs(4326)
# compute bboxes and find width of the widest one
bboxes <- lapply(sf::st_geometry(states6),
FUN = function(x) as.numeric(st_bbox((x))))
which_max_wid <- which.max(lapply(bbs, FUN = function(x) abs(x[1] - x[3])))
max_wid <- bbs[[which_max_wid]][1] - bbs[[which_max_wid]][3]
# create some fake points, at a distance of max_wid/2 from
# centroids of each state, then a multipoint by state_name
fake_points_min <- st_sf(name_state = states6$name_state,
geometry = st_geometry(sf::st_centroid(states6)) - c(max_wid/2, 0))
fake_points_max <- st_sf(name_state = states6$name_state,
geometry = st_geometry(sf::st_centroid(states6)) + c(max_wid/2, 0))
fake_points <- rbind(fake_points_min,fake_points_max) %>%
dplyr::group_by(name_state) %>%
dplyr::summarize() %>%
dplyr::ungroup() %>%
sf::st_set_crs(4326)
# plot
plot <- tm_shape(states6) +
tm_graticules() +
tm_borders(col='black') +
tm_fill(col='black') +
tm_facets(by = "name_state", ncol=3) +
tm_scale_bar(breaks = c(0, 150, 300), text.size = 3) +
tm_shape(fake_points) + #here we add the point layer to force constant width!
tm_dots(alpha = 0)+
tm_facets(by = "name_state", ncol=3)
plot
, giving:
回答3:
Most of the times I prefer plot for sf
library(sf)
library(geobr)
# Read all Brazilian states
states <- geobr::read_state(code_state = 'all', year=2015)
# Select six states
states6 <- subset(states, code_state %in% c(35,33,53,29,31,23))
par(mfrow = c(2, 3))
for(i in 1:nrow(states6)){
plot(states6$geometry[i], axes = T, main = states6$name_state[i])
}
par(mfrow = c(1,1))
However, removing the axis can be also effective
par(mfrow = c(2, 3))
for(i in 1:nrow(states6)){
plot(states6$geometry[i], axes = F, main = states6$name_state[i])
axis(1)
axis(2)
}
par(mfrow = c(1,1))
As probably you would want to add a background, add the option reset = FALSE as explained here and you can add several other sf or stars objects
EDIT1: You could also try imagemagick
library(ggplot2)
imas <- paste0(letters[1:6], ".png")
for(i in 1:nrow(states6)) {
png( imas[i])
print(
ggplot(states6[i,]) +
geom_sf() +
ggtitle(states6$name_state[i])
)
dev.off()
}
library(magick)
a <- image_append(image = c(image_read(imas[1]),
image_read(imas[2]),
image_read(imas[3])))
b <- image_append(image = c(image_read(imas[4]),
image_read(imas[5]),
image_read(imas[6])))
image_append(c(a,b), stack = T)
来源：https://stackoverflow.com/questions/58549852/small-multiple-maps-with-geom-sf-at-the-same-spatial-scale