The tilemaps package implements an algorithm for
generating maps, known as tile maps, in which each region is represented
by a single tile of the same shape and size. When creating a tile map,
the goal is to arrange tiles in a manner that preserves local
relationships between regions, as well as the overall shape of the
original map. The algorithm implemented in this package was proposed by
Graham McNeill and Scott Hale in the paper “Generating Tile
Maps” (2017). Using a tile map is advantageous when trying to
visualize data where the importance of a region does not depend on the
geographic area of the region. Tile maps prevent regions with large
areas from dominating a map and prevent regions with small areas from
going unnoticed. The package allows the user to generate a single tile
map or many tile maps, which can be compared by using cost functions or
by plotting the maps.
You can install the latest release from CRAN with:
install.packages("tilemaps")You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("kaerosen/tilemaps")To create a single tile map, the generate_map() function
can be used. In the following example, a tile map with flat-topped
hexagons is generated for the contiguous United States using the
governors dataset, which is part of the
tilemaps package.
library(tilemaps)
library(sf)
library(dplyr)
library(ggplot2)
governors <- governors %>%
mutate(tile_map = generate_map(geometry, square = FALSE, flat_topped = TRUE))
ggplot(governors) +
geom_sf(aes(geometry = tile_map)) +
geom_sf_text(aes(geometry = tile_map, label = abbreviation),
fun.geometry = function(x) st_centroid(x)) +
theme_void()
The generate_map() function requires an object of class
sfc_POLYGON or sfc_MULTIPOLYGON as input. If
the coordinates of the sfc object are in terms of longitude
and latitude, the coordinates will need to be transformed to a planar
projection before creating the tile map. The square
argument controls whether the tiles are squares or hexagons, and the
flat_topped argument controls whether or not hexagons are
flat-topped. The generate_map() function only works for
contiguous regions. However, after a tile map has been generated, the
create_island() function can be used to add islands to the
layout of the tile map.
all_states <- governors %>%
add_row(abbreviation = "AK", party = "Republican",
tile_map = create_island(governors$tile_map, "lower left")) %>%
add_row(abbreviation = "HI", party = "Democrat",
tile_map = create_island(governors$tile_map, c(-12050000, 3008338)))
ggplot(all_states) +
geom_sf(aes(geometry = tile_map)) +
geom_sf_text(aes(geometry = tile_map, label = abbreviation),
fun.geometry = function(x) st_centroid(x)) +
theme_void()
Once a tile map has been created, coloring tiles according to another variable is simple. In the following code, the states are colored according to the party affiliation of the governor. This is an example of a situation where it is useful to use a tile map, instead of a regular map, because each state has only one governor, regardless of the area or population of the state.
ggplot(all_states) +
geom_sf(aes(geometry = tile_map, fill = party)) +
geom_sf_text(aes(geometry = tile_map, label = abbreviation),
fun.geometry = function(x) st_centroid(x)) +
scale_fill_brewer(palette = "Set1") +
ggtitle("Party Affiliation of United States Governors (2020)") +
theme_void()
To create and compare more than one tile map, the
many_maps() function can be used. In the following example,
16 candidate tile maps are generated and plotted.
us_maps <- many_maps(governors$geometry, governors$abbreviation,
prop = c(0, 0.1), interpolate = c(0.5, 1),
smoothness = c(0, 20), shift = list(c(0,0), c(0,0.5)))
The prop, interpolate,
smoothness, and shift arguments add variation
at different steps in the algorithm to create different candidate tile
maps. The total number of maps generated by the many_maps()
function is the product of the lengths of these arguments. The output of
the many_maps() function is a data frame in which each row
corresponds to one map and the columns contain the generated maps, the
parameters used for creating the maps, and the costs associated with
each map. The different sources of variation and types of costs are
discussed in the tilemaps vignette.
The plot of all the candidates maps shown above can be generated
using the plot_many_maps() function. The function requires
a list of maps, which are of class sfc_POLYGON, and the
labels for the regions of the map. Below is code for how the
plot_many_maps() function can be used to create the same
plot as before.
plot_many_maps(us_maps$map, governors$abbreviation)McNeill, Graham, and Scott A Hale. 2017. “Generating Tile Maps.” In Computer Graphics Forum, 36:435–45. 3. Wiley Online Library.