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Create a ggplot2 visualization of hexagonal grid cells

Source: R/hexify_map.R
hexify_heatmap.Rd

Creates a ggplot2-based visualization of hexagonal grid cells, optionally colored by a value column. Supports continuous and discrete color scales, projection transformation, and customizable styling.

Usage

hexify_heatmap(
  data,
  value = NULL,
  basemap = NULL,
  crs = NULL,
  colors = NULL,
  breaks = NULL,
  labels = NULL,
  hex_border = "#5D4E37",
  hex_lwd = 0.3,
  hex_alpha = 0.7,
  basemap_fill = "gray90",
  basemap_border = "gray50",
  basemap_lwd = 0.5,
  mask_outside = FALSE,
  aperture = 3L,
  xlim = NULL,
  ylim = NULL,
  title = NULL,
  legend_title = NULL,
  na_color = "gray90",
  theme_void = TRUE
)

Arguments

data

A HexData object from hexify(), a data frame with cell_id and cell_area columns, or an sf object with hexagon polygons.

value

Column name (as string) to use for fill color. If NULL, cells are drawn with a uniform fill color. If not specified but data has a 'count' or 'n' column, that will be used automatically.

basemap

Optional basemap. Can be:

  • NULL: No basemap (default)

  • "world": Use built-in hexify_world map (low resolution)

  • "world_hires": Use high-resolution map from rnaturalearth (requires package)

  • An sf object: User-supplied vector map

crs

Target CRS for the map projection. Can be:

  • A numeric EPSG code (e.g., 4326 for WGS84, 3035 for LAEA Europe)

  • A proj4 string

  • An sf crs object

  • NULL to use WGS84 (EPSG:4326)

colors

Color palette for the heatmap. Can be:

  • A character vector of colors (for manual scale)

  • A single RColorBrewer palette name (e.g., "YlOrRd", "Greens")

  • NULL to use viridis

breaks

Numeric vector of break points for binning continuous values, or NULL for continuous scale. Use Inf and -Inf for open-ended bins.

labels

Labels for the breaks (length should be one less than breaks). If NULL, labels are auto-generated.

hex_border

Border color for hexagons

hex_lwd

Line width for hexagon borders

hex_alpha

Transparency for hexagon fill (0-1)

basemap_fill

Fill color for basemap polygons

basemap_border

Border color for basemap polygons

basemap_lwd

Line width for basemap borders

mask_outside

Logical. If TRUE and basemap is provided, mask hexagon portions that fall outside the basemap polygons.

aperture

Grid aperture (default 3), used if data is from hexify()

xlim

Optional x-axis limits (in target CRS units) as c(min, max)

ylim

Optional y-axis limits (in target CRS units) as c(min, max)

title

Plot title

legend_title

Title for the color legend

na_color

Color for NA values

theme_void

Logical. If TRUE (default), use a minimal theme without axes, gridlines, or background.

Value

A ggplot2 object that can be further customized or saved.

Details

This function provides publication-quality heatmap visualizations of hexagonal grids using ggplot2. It returns a ggplot object that can be further customized with standard ggplot2 functions.

Color Scales

The function supports three types of color scales:

Continuous

Set breaks = NULL for a continuous gradient

Binned

Provide breaks vector to bin values into categories

Discrete

If value column is a factor, discrete colors are used

Projections

Common projections:

4326

WGS84 (unprojected lat/lon)

3035

LAEA Europe

3857

Web Mercator

"+proj=robin"

Robinson (world maps)

"+proj=moll"

Mollweide (equal-area world maps)

See also

plot_grid for base R plotting, cell_to_sf to generate polygons manually

Other visualization: plot_world()

Examples

if (FALSE) { # \dontrun{
library(hexify)
library(ggplot2)

# Sample data with counts
cities <- data.frame(
  lon = c(16.37, 2.35, -3.70, 12.5, 4.9),
  lat = c(48.21, 48.86, 40.42, 41.9, 52.4),
  count = c(100, 250, 75, 180, 300)
)
result <- hexify(cities, lon = "lon", lat = "lat", area_km2 = 5000)

# Simple plot (uniform fill, no value mapping)
hexify_heatmap(result, basemap = "world")

# Heatmap with value mapping
hexify_heatmap(result, value = "count")

# With world basemap and custom colors
hexify_heatmap(result, value = "count",
               basemap = "world",
               colors = "YlOrRd",
               title = "City Density")

# Binned values with custom breaks
hexify_heatmap(result, value = "count",
               basemap = "world",
               breaks = c(-Inf, 100, 200, Inf),
               labels = c("Low", "Medium", "High"),
               colors = c("#fee8c8", "#fdbb84", "#e34a33"))

# Different projection (LAEA Europe)
hexify_heatmap(result, value = "count",
               basemap = "world",
               crs = 3035,
               xlim = c(2500000, 6500000),
               ylim = c(1500000, 5500000))

# Customize further with ggplot2
hexify_heatmap(result, value = "count", basemap = "world") +
  labs(caption = "Data source: Example") +
  theme(legend.position = "bottom")
} # }