Dimension reduction
R-bloggers 2025-11-06
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Day 6 of 30DayMapChallenge: « Dimensions » (previously).
According to Wikipedia, Uniform manifold approximation and projection (UMAP) is a nonlinear dimensionality reduction technique. It will allow us to project many dimensions (well, only 3 in this example) onto a 2D plane.
library(sf)library(umap)library(dplyr)library(tidyr)library(ggplot2)library(ggrepel)library(glue)options(scipen = 100)
Data
We’ll use the french communes (get the data from this post).
com <- read_sf("~/data/adminexpress/adminexpress_cog_simpl_000_2022.gpkg", layer = "commune") |> st_centroid() |> mutate(x = st_coordinates(geom)[, 1], y = st_coordinates(geom)[, 2])UMAP
The dimensions taken into account are: location (x, y) and population. These variables should be scaled but the result is prettier without scaling…
umaps_params <- umap.defaultsumaps_params$random_state <- 20251106com_umap <- com |> st_drop_geometry() |> select(x, y, population) |> # scale() |> umap(config = umaps_params)res <- com_umap$layout |> as_tibble(.name_repair = "universal") |> bind_cols(com) |> rename(UMAP1 = 1, UMAP2 = 2)
Map
res |> ggplot(aes(UMAP1, UMAP2, color = population)) + geom_point() + geom_text_repel(data = filter(res, statut %in% c("Préfecture", "Préfecture de région", "Capitale d'état")), aes(label = nom), size = 3, force = .5, force_pull = 0.5, max.overlaps = 1e6, bg.colour = "#ffffffaa", bg.r = .2, alpha = .6) + scale_color_viridis_c(trans = "log1p", option = "H", breaks = c(1000, 50000, 500000, 2000000)) + coord_equal() + labs(title = "Uniform manifold approximation and projection of french communes", subtitle = "by location and population", caption = glue("https://r.iresmi.net/ - {Sys.Date()} data from IGN Adminexpress 2022")) + theme_minimal() + theme(plot.caption = element_text(size = 6, color = "darkgrey"))
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