Title:	Customizable China Map Visualizations
Version:	0.2.0
Description:	A 'ggplot2' extension for visualizing China’s map, offering customizable projections, boundary styles, and buffer zones for thematic maps. Suitable for spatial data analysis and enhancing map visualization with flexible styling options.
License:	GPL-3
Encoding:	UTF-8
Depends:	R (≥ 3.5.0), ggplot2 (≥ 3.3.0)
Imports:	sf (≥ 1.0.0), dplyr (≥ 1.1.0), terra (≥ 1.7), tidyterra (≥ 0.6.0), curl (≥ 5.0.0), rlang, digest, grid
URL:	https://rimagination.github.io/ggmapcn/
BugReports:	https://github.com/Rimagination/ggmapcn/issues
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
VignetteBuilder:	knitr
Config/testthat/edition:	3
RoxygenNote:	7.3.2
NeedsCompilation:	no
Packaged:	2025-10-10 08:56:03 UTC; Administrator
Author:	Liang Ren [aut, cre]
Maintainer:	Liang Ren <rl23@mails.tsinghua.edu.cn>
Repository:	CRAN
Date/Publication:	2025-10-10 11:10:02 UTC

ggmapcn: Customizable China Map Visualizations

Description

A 'ggplot2' extension for visualizing China’s map, offering customizable projections, boundary styles, buffer zones, and annotation layers such as compass and scale bars.

Details

Main features: - Projection-aware compass ('annotation_compass') and scale bar ('annotation_scalebar'). - Built-in geodata management via 'check_geodata'. - Multiple compass styles (classic, rose, Sinan, guiding fish, etc.). - Easy integration with ggplot2 and sf workflows.

Author(s)

Maintainer: Liang Ren rl23@mails.tsinghua.edu.cn (ORCID)

See Also

Useful links:

• https://rimagination.github.io/ggmapcn/

• Report bugs at https://github.com/Rimagination/ggmapcn/issues

Add a Spatially-Aware Compass

Description

'annotation_compass()' adds a compass (north arrow) to a 'ggplot2' map. It can be aligned to **grid north** (top of the plot) or **true north** (geographic north). Styles can be supplied as a grob or a function returning a grob (e.g., 'north_arrow_classic()', 'compass_sinan()').

Usage

annotation_compass(
  mapping = NULL,
  data = NULL,
  ...,
  location = "bl",
  which_north = "grid",
  height = unit(1.5, "cm"),
  width = unit(1.5, "cm"),
  pad_x = unit(0.5, "cm"),
  pad_y = unit(0.5, "cm"),
  rotation = NULL,
  style = north_arrow_classic()
)

Arguments

Details

* '"grid"' north: compass points straight up in the plotting space (no CRS needed). * '"true"' north: compass rotates toward geographic North Pole using the plot CRS. This requires a valid CRS available via 'coord_sf()' or injected by setting 'layer$geom_params$crs'. * You can override any auto-rotation by providing 'rotation' (degrees CCW). * The layer is annotation-like: it draws once per panel using the panel bounds.

Value

A 'ggplot2' layer object.

See Also

[compass-styles]

Examples

nc <- sf::st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)

base <- ggplot2::ggplot() +
  ggplot2::geom_sf(data = nc, fill = "grey90") +
  ggplot2::theme_minimal()

# Example 1: Grid north (no CRS required), bottom-left
base + annotation_compass()

# Example 2: Custom style & position (top-left)
base + annotation_compass(location = "tl", style = compass_sinan())

# Example 3: True north (requires a CRS)
base +
  ggplot2::coord_sf(crs = "+proj=lcc +lon_0=-100 +lat_1=33 +lat_2=45") +
  annotation_compass(which_north = "true")

Add a Spatially-Aware Scale Bar

Description

[annotation_scalebar()] adds a projection-aware scale bar to a [ggplot2::ggplot2-package] map. It detects the map's CRS and chooses a readable width and units automatically. Robust fallbacks prevent "zero-length unit" errors and allow the scale bar to render even when CRS information is limited.

Supported styles: - '"segment"' (minimal horizontal bar with ticks and labels) - '"ticks"' (baseline + vertical ticks) - '"bar"' (alternating black/white blocks)

Usage

annotation_scalebar(
  mapping = NULL,
  data = NULL,
  ...,
  location = "bl",
  style = "segment",
  fixed_width = NULL,
  crs_unit = NULL,
  crs = NULL,
  display_unit = NULL,
  unit_labels = NULL,
  width_hint = 0.25,
  unit_category = "metric",
  bar_cols = c("black", "white"),
  line_width = 1,
  height = grid::unit(0.25, "cm"),
  pad_x = grid::unit(0.25, "cm"),
  pad_y = grid::unit(0.25, "cm"),
  text_pad = grid::unit(0.15, "cm"),
  text_cex = 0.7,
  text_face = NULL,
  text_family = "",
  tick_height = 0.6,
  segments = NULL,
  label_show = "ends",
  minor_tick_height = 0.5,
  geographic_mode = c("approx_m", "degrees"),
  text_col = "black",
  line_col = "black"
)

Arguments

Details

* If a **projected CRS** is in use (e.g., UTM/AEQD with meters), the scale bar is accurate in native units. * If a **geographic CRS** (EPSG:4326, degrees) is in use, distances vary with latitude. The 'geographic_mode' parameter controls how to display the scale: - '"approx_m"' (default): approximate meters/kilometers using great-circle distance at the panel's center latitude. A warning is issued. - '"degrees"': display raw degree units (e.g., '1°') without converting to meters. * You can also override the width with 'fixed_width' (in native CRS units).

Value

A 'ggplot2' layer object representing the scale bar.

Dependencies

Requires **ggplot2**, **sf**, and **grid**.

Examples

nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)

base_plot <- ggplot2::ggplot() +
  ggplot2::geom_sf(data = nc, fill = "grey90") +
  ggplot2::theme_minimal()

# Example 1: Projected CRS with a longer scale bar
base_plot + ggplot2::coord_sf(crs = 32617) +
  annotation_scalebar(location = "bl", width_hint = 0.5)

# Example 2: Ticks style, top-right (now correctly rendered)
base_plot + ggplot2::coord_sf(crs = 32617) +
  annotation_scalebar(location = "tr", style = "ticks")

# Example 3: Geographic CRS (EPSG:4326), approximate meters (warns)
base_plot + ggplot2::coord_sf(crs = 4326) +
  annotation_scalebar(location = "bl", geographic_mode = "approx_m")

# Example 4: Force a 100 km bar with red lines (now works correctly)
base_plot + ggplot2::coord_sf(crs = 32617) +
  annotation_scalebar(location = "bl", fixed_width = 100000, display_unit = "km",
                      line_col = "red")

Elevation Map of China Layer for ggplot2

Description

'basemap_dem' adds a digital elevation model (DEM) raster map of China as a layer to ggplot2. The function ensures the output map remains rectangular, regardless of the chosen projection. It supports displaying the DEM either within China's boundary or in a larger rectangular area around China. Users can provide their own DEM data using the 'data' parameter, or the default built-in DEM data will be used.

Usage

basemap_dem(
  data = NULL,
  crs = NULL,
  within_china = FALSE,
  maxcell = 1e+06,
  na.rm = FALSE,
  ...
)

Arguments

Value

A 'ggplot' object containing the elevation map of China as a layer, which can be further customized or plotted.

See Also

geom_boundary_cn

Examples

# Before using the basemap_dem function, make sure the required data files are available.
# The required files are: "gebco_2024_China.tif" and "China_mask.gpkg".
# You can use check_geodata() to download them from GitHub if they are not available locally.

# Check and download the required data files if they are missing
check_geodata(files = c("gebco_2024_China.tif", "China_mask.gpkg"))

# Define the CRS for China (EPSG:4326 is a common global geographic coordinate system)
china_proj <- "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs"

# Example 1: Display full rectangular area around China using built-in DEM data
ggplot() +
  basemap_dem(within_china = FALSE) +
  tidyterra::scale_fill_hypso_tint_c(
    palette = "gmt_globe",
    breaks = c(-10000, -5000, 0, 2000, 5000, 8000)
  ) +
  theme_minimal()

# Example 2: Display only China's DEM and boundaries using built-in DEM data
ggplot() +
  basemap_dem(crs = china_proj, within_china = TRUE) +
  geom_boundary_cn(crs = china_proj) +
  tidyterra::scale_fill_hypso_c(
    palette = "dem_print",
    breaks = c(0, 2000, 4000, 6000),
    limits = c(0, 7000)
  ) +
  labs(fill = "Elevation (m)") +
  theme_minimal()

Vegetation Map of China Layer for ggplot2

Description

Adds a vegetation raster map of China to a ggplot2 plot, with color-coded vegetation types.

Usage

basemap_vege(
  color_table = NULL,
  crs = NULL,
  maxcell = 1e+06,
  use_coltab = TRUE,
  na.rm = FALSE,
  ...
)

Arguments

Value

A ggplot2 layer object representing the vegetation map of China.

References

Zhang X, Sun S, Yong S, et al. (2007). *Vegetation map of the People's Republic of China (1:1000000)*. Geology Publishing House, Beijing.

Examples

# Example1: Check and load the vegetation raster map

# Make sure the required raster data is available
check_geodata(files = c("vege_1km_projected.tif"))

# Once the data is checked or downloaded, add the vegetation raster to a ggplot
ggplot() +
  basemap_vege() +
  theme_minimal()

# Example2: Customize color table
custom_colors <- data.frame(
  code = 0:11,
  type = c(
    "Non-vegetated", "Needleleaf forest", "Needleleaf and broadleaf mixed forest",
    "Broadleaf forest", "Scrub", "Desert", "Steppe", "Grassland",
    "Meadow", "Swamp", "Alpine vegetation", "Cultivated vegetation"
  ),
  col = c(
    "#8D99B3", "#97B555", "#34BF36", "#9ACE30", "#2EC6C9", "#E5CE0E",
    "#5BB1ED", "#6494EF", "#7AB9CB", "#D97A80", "#B87701", "#FEB780"
  )
)
ggplot() +
  basemap_vege(color_table = custom_colors) +
  labs(fill = "Vegetation type group") +
  theme_minimal()

Check and Download Geospatial Data

Description

Ensure required geodata files exist locally. The function searches and reuses existing files (when overwrite = FALSE) before attempting any network download, in the following order:

1. user-provided local_dirs

2. installed package extdata (even if not writable)

3. per-user cache tools::R_user_dir("ggmapcn","data")

If no valid local file is found (or overwrite = TRUE), the function downloads from mirrors in order. By default, a China-friendly CDN (jsDelivr) is tried first, then GitHub raw.

Robust features: multiple mirrors, atomic writes, resume, timeouts, retries, safe checksum checks, and correct curl progress callback.

Usage

check_geodata(
  files = NULL,
  overwrite = FALSE,
  quiet = FALSE,
  max_retries = 3,
  mirrors = NULL,
  use_checksum = TRUE,
  checksums = NULL,
  resume = TRUE,
  local_dirs = NULL
)

Arguments

Value

Character vector of absolute file paths (NA for failures).

Examples

# Basic: ensure default files exist
check_geodata()

# Single file: reuse existing file if present (default overwrite = FALSE)
check_geodata(files = "boundary.rda")

# Force re-download a file (e.g., suspected corruption)
check_geodata(files = "boundary.rda", overwrite = TRUE)

# Search local folders first; skip download if a valid file is found there
check_geodata(
  files = c("boundary.rda", "world.rda"),
  local_dirs = c(getwd())  # add more directories if needed
)

# Provide your own mirror order (first tried wins)
check_geodata(
  files = "boundary.rda",
  mirrors = c(
    "https://cdn.jsdelivr.net/gh/Rimagination/ggmapcn-data@main/data/",
    "https://raw.githubusercontent.com/Rimagination/ggmapcn-data/main/data/"
  )
)

Coordinate System with Transformed Limits for Custom Projections

Description

'coord_proj' is a wrapper around ggplot2::coord_sf(). It simplifies specifying map limits ('xlim', 'ylim') in longitude and latitude (WGS84 CRS) and automatically transforms them into the specified CRS for accurate projections.

This function extends the functionality of coord_sf() to seamlessly handle user-specified geographic boundaries in any projection, ensuring accurate mapping.

Usage

coord_proj(
  crs = NULL,
  xlim = NULL,
  ylim = NULL,
  expand = TRUE,
  default_crs = "EPSG:4326",
  ...
)

Arguments

Value

A ggplot2 coord_sf object with the transformed limits.

See Also

ggplot2::coord_sf, geom_world

Examples

# World map with default projection and limits
ggplot() +
  geom_world() +
  coord_proj(
    crs = "+proj=longlat +datum=WGS84",
    xlim = c(-180, 180),
    ylim = c(-90, 90),
    expand=FALSE
  ) +
  theme_minimal()

# Focused view with Azimuthal Equidistant projection
china_proj <- "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs"
ggplot() +
  geom_world(fill = "lightblue") +
  coord_proj(
    crs = china_proj,
    xlim = c(60, 140),
    ylim = c(-10, 50)
  ) +
  theme_minimal()

# Display a small map of the South China Sea Islands with a custom projection
ggplot() +
  geom_boundary_cn() +
  theme_bw() +
  coord_proj(
    crs = china_proj,
    expand = FALSE,
    xlim = c(105, 123),
    ylim = c(2, 23)
  )

Plot Boundaries of China

Description

Draw China's administrative boundaries and optional map decorations (compass and scale bar). Each boundary category (mainland, coastline, provinces, etc.) can be styled independently. The data are reprojected to the specified CRS before plotting.

Usage

geom_boundary_cn(
  crs = "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs",
  compass = FALSE,
  scale = FALSE,
  mainland_color = "black",
  mainland_size = 0.5,
  mainland_linetype = "solid",
  coastline_color = "blue",
  coastline_size = 0.3,
  coastline_linetype = "solid",
  ten_segment_line_color = "black",
  ten_segment_line_size = 0.5,
  ten_segment_line_linetype = "solid",
  SAR_boundary_color = "grey40",
  SAR_boundary_size = 0.5,
  SAR_boundary_linetype = "dashed",
  undefined_boundary_color = "black",
  undefined_boundary_size = 0.5,
  undefined_boundary_linetype = "longdash",
  province_color = "transparent",
  province_size = 0.3,
  province_linetype = "solid",
  ...
)

Arguments

Value

A list of 'ggplot2' layers.

Examples

# Example 1: Basic China map
ggplot() +
  geom_boundary_cn() +
  theme_minimal()

# Example 2: Add compass and scale bar (easy mode)
ggplot() +
  geom_boundary_cn(compass = TRUE, scale = TRUE) +
  theme_minimal()

# Example 3: Custom styling
ggplot() +
  geom_boundary_cn(
    coastline_color = "steelblue",
    province_color = "grey70",
    province_linetype = "dashed"
  ) +
  theme_minimal()

# Example 4: Advanced usage with a custom projected CRS
Albers <-  "+proj=aea +lat_1=25 +lat_2=47 +lat_0=0 +lon_0=105 +x_0=0 +y_0=0 +
+ datum=WGS84 +units=m +no_defs"

ggplot() +
  geom_boundary_cn(crs = Albers) +
  annotation_compass(location = "tl", which_north = "true") +
  annotation_scalebar(location = "bl", fixed_width = 500000, display_unit = "km") +
  coord_sf(crs = Albers) +
  theme_minimal()

Plot Buffered Layers for China's Boundary

Description

Creates a ggplot2 layer for displaying buffered areas around China's boundaries, including both the mainland boundary and the ten-segment line. Buffers with user-defined distances are generated around each boundary, providing flexibility in projection and appearance.

Usage

geom_buffer_cn(
  mainland_dist = 20000,
  ten_line_dist = NULL,
  crs = "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs",
  color = NA,
  fill = "#D2D5EB",
  ...
)

Arguments

Value

A ggplot2 layer displaying buffered areas around China's boundaries, with customizable buffer distances for the mainland boundary and the ten-segment line, using the specified projection.

Examples

# Plot buffers with specified distances for mainland and ten-segment line
ggplot() +
  geom_buffer_cn(
    mainland_dist = 10000,
    ten_line_dist = 5000
  ) +
  theme_minimal()

Visualize Spatial Point Data

Description

'geom_loc' is a wrapper around ggplot2::geom_sf() designed for visualizing spatial point data. It supports both sf objects and tabular data frames with longitude and latitude columns, automatically transforming them into the specified coordinate reference system (CRS).

Usage

geom_loc(
  data,
  lon = NULL,
  lat = NULL,
  crs = "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs",
  mapping = ggplot2::aes(),
  ...
)

Arguments

Details

This function simplifies the process of visualizing spatial data in ggplot2 by automatically handling CRS transformations and providing an interface for both sf and tabular data. If the input is a tabular data frame, it will be converted to an sf object using the specified longitude and latitude columns.

See ggplot2::geom_sf() for details on additional parameters and aesthetics.

Value

A ggplot2 layer for visualizing spatial point data, either from an 'sf' object or a tabular data frame with longitude and latitude columns, after transforming the data to the specified coordinate reference system (CRS).

See Also

geom_boundary_cn

Examples

# Generate a random dataset with latitude and longitude
set.seed(123)
data_sim <- data.frame(
  Longitude = runif(100, 80, 120),
  Latitude = runif(100, 28, 40),
  Category = sample(c("Type A", "Type B", "Type C"), 100, replace = TRUE)
)

# Visualize the data with China's boundaries
ggplot() +
  geom_boundary_cn() +
  geom_loc(
    data = data_sim, lon = "Longitude", lat = "Latitude",
    mapping = aes(color = Category), size = 1, alpha = 0.7
  ) +
  theme_minimal()

Plot China Map with Customizable Options

Description

‘geom_mapcn()' plots China’s administrative boundaries with a simple, opinionated interface. It loads packaged map data when 'data' is 'NULL', removes the special row labeled '"Boundary Line"', supports optional attribute-based filtering, and can reproject to a user-specified CRS.

Usage

geom_mapcn(
  data = NULL,
  admin_level = "province",
  crs = "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs",
  color = "black",
  fill = "white",
  linewidth = 0.5,
  filter_attribute = NULL,
  filter = NULL,
  mapping = NULL,
  ...
)

Arguments

Value

A 'ggplot2' layer.

Examples

# Basic provincial map
ggplot2::ggplot() +
  geom_mapcn() +
  ggplot2::theme_minimal()

# Filter by names stored in the data (e.g., English names)
ggplot2::ggplot() +
  geom_mapcn(filter_attribute = "name_en",
             filter = c("Beijing", "Shanghai"),
             fill = "red") +
  ggplot2::theme_minimal()

# Use a different projection
ggplot2::ggplot() +
  geom_mapcn(crs = "+proj=merc", linewidth = 0.7) +
  ggplot2::theme_minimal()

Plot World Map with Customizable Options

Description

A wrapper around [ggplot2::geom_sf()] for visualizing world maps with customizable options. This function allows for custom projections, filtering specific countries or regions, and detailed aesthetic customizations for borders and fills.

Usage

geom_world(
  data = NULL,
  crs = "+proj=longlat +datum=WGS84",
  color = "black",
  fill = "white",
  linewidth = 0.5,
  filter_attribute = "SOC",
  filter = NULL,
  ...
)

Arguments

Details

This function simplifies the process of creating world maps by combining the functionality of 'geom_sf' with user-friendly options for projections, filtering, and custom styling. Key features include: - **Custom projections**: Easily apply any CRS to the map. - **Filtering by attributes**: Quickly focus on specific countries or regions. - **Flexible aesthetics**: Customize fill, borders, transparency, and other visual properties.

Value

A 'ggplot2' layer for world map visualization.

See Also

[ggplot2::geom_sf()], [sf::st_transform()], [sf::st_read()]

Examples

  # Plot the default world map
  ggplot() +
    geom_world() +
    theme_minimal()

  # Using Robinson projection with central meridian at 0°
  ggplot() +
    geom_world(crs = "+proj=robin +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m") +
    theme_minimal()

  # Filter specific countries (e.g., China and its neighbors)
  china_neighbors <- c("CHN", "AFG", "BTN", "MMR", "LAO", "NPL", "PRK", "KOR",
                       "KAZ", "KGZ", "MNG", "IND", "BGD", "TJK", "PAK", "LKA", "VNM")
  ggplot() +
    geom_world(filter = china_neighbors) +
    theme_minimal()

  # Background map + Highlight specific region
  ggplot() +
    geom_world(fill = "gray80", color = "gray50", alpha = 0.5) +
    geom_world(filter = c("CHN"), fill = "red", color = "black", linewidth = 1.5) +
    theme_minimal()

  # Customize styles with transparency and bold borders
  ggplot() +
    geom_world(fill = "lightblue", color = "darkblue", linewidth = 1, alpha = 0.8) +
    theme_void()

Classic North Arrow Style (Minimal)

Description

A collection of style constructors that return 'grid' grobs for use with 'annotation_compass(style = ...)'. These styles provide different visual appearances for a compass or north arrow drawn as an annotation.

Usage

north_arrow_classic(
  fill = c("white", "black"),
  line_col = "black",
  line_width = 2,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_sinan(
  line_col = "black",
  square_pad = 0.1,
  ring_outer = 0.35,
  ring_ratio = 0.65,
  labels = c("N", "E", "S", "W"),
  text_size = 12,
  text_face = "plain",
  text_family = "",
  text_col = "black",
  label_offset = 0.05,
  spoon_fill = "black",
  spoon_col = "black",
  spoon_scale = 0.8,
  inner_fill = "lightgrey",
  square_width = 2,
  outer_width = 2,
  inner_width = 1,
  spoon_width = 1
)

north_arrow_classic(
  fill = c("white", "black"),
  line_col = "black",
  line_width = 2,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

north_arrow_solid(
  fill = "black",
  line_col = "black",
  line_width = 1,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_rose_simple(
  fill = c("white", "black"),
  line_col = "black",
  line_width = 1,
  sharpness = 0.7,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_rose_classic(
  fill = c("white", "black"),
  line_col = "black",
  line_width = 1.5,
  sharpness = 0.6,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_rose_circle(
  fill = "white",
  line_col = "black",
  line_width = 3,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_guiding_fish(
  size = 1,
  ring_ratio = 0.2,
  ring_width = 2,
  n_seg = 16,
  fish_col = "black",
  fish_shift = -0.03,
  text_col = "black",
  text_size = 12,
  text_face = "plain",
  text_family = ""
)

compass_sinan(
  line_col = "black",
  square_pad = 0.1,
  ring_outer = 0.35,
  ring_ratio = 0.65,
  labels = c("N", "E", "S", "W"),
  text_size = 12,
  text_face = "plain",
  text_family = "",
  text_col = "black",
  label_offset = 0.05,
  spoon_fill = "black",
  spoon_col = "black",
  spoon_scale = 0.8,
  inner_fill = "lightgrey",
  square_width = 2,
  outer_width = 2,
  inner_width = 1,
  spoon_width = 1
)

Arguments

Details

Exported constructors documented under this topic:

• north_arrow_classic()

• north_arrow_solid()

• compass_rose_simple()

• compass_rose_classic()

• compass_rose_circle()

• compass_guiding_fish()

• compass_sinan()

Each constructor returns a grob ready to be passed to annotation_compass(style = ...). All styles include an "N" (or cardinal labels) to indicate north.

Value

A 'grid' graphical object (grob).

See Also

[annotation_compass] for adding the compass to a ggplot.

Examples

# Standalone preview
grid::grid.newpage(); grid::grid.draw(north_arrow_classic())
grid::grid.newpage(); grid::grid.draw(north_arrow_solid())
grid::grid.newpage(); grid::grid.draw(compass_rose_simple())
grid::grid.newpage(); grid::grid.draw(compass_rose_classic())
grid::grid.newpage(); grid::grid.draw(compass_rose_circle())
grid::grid.newpage(); grid::grid.draw(compass_guiding_fish())
grid::grid.newpage(); grid::grid.draw(compass_sinan())

# Use in ggplot

if (requireNamespace("ggplot2", quietly = TRUE) &&
    requireNamespace("sf", quietly = TRUE)) {
  nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
  p <- ggplot2::ggplot() +
    ggplot2::geom_sf(data = nc, fill = "grey90") +
    ggplot2::theme_minimal()

  p + annotation_compass(location = "tr", style = north_arrow_classic())
  p + annotation_compass(location = "bl", style = compass_sinan())
}