• Stars
    star
    361
  • Rank 117,538 (Top 3 %)
  • Language
    R
  • License
    Other
  • Created over 4 years ago
  • Updated 4 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

ggplot geoms with pattern fills
output
github_document

ggpattern

CRAN Status Badge R build status

ggpattern provides custom ggplot2 geoms which support filled areas with geometric and image-based patterns.

Reading the articles/vignettes on the package website is probably the best way to get started.

Feature Summary

  • Custom versions of (almost) all the geoms from ggplot2 which have a region which can be filled.
  • A suite of aesthetics for controlling the pattern appearance (e.g. pattern_alpha)
  • The ability to include user-defined patterns

Installation

You can install the development version from GitHub with the following instructions:

# install.packages("remotes")
remotes::install_github("trevorld/ggpattern")

You can install the CRAN release version using:

install.packages("ggpattern")

Do note though that due to CRAN size limitations the CRAN version omits several vignettes that are contained in the development version.

An installation error is highly unlikely to be an issue with {ggpattern} itself. Please don't open up a Github Issues unless you are sure it is an issue with {ggpattern} itself. If you have an error installing the package we strongly suggest that you look at all your error messages more closely to figure out which package dependency is failing to install and why. See https://thomasadventure.blog/posts/install-r-packages/ for more info on installing R packages.

Quickstart

  1. Take an existing plot which contains a geom with a fillable area e.g geom_col().
  2. Use the {ggpattern} version of the geom e.g. ggpattern::geom_col_pattern() instead of ggplot2::geom_col()
  3. Set the aesthetic pattern to your choice of pattern e.g pattern = 'stripe', and set other options using pattern_* aesthetics
df <- data.frame(level = c("a", "b", "c", 'd'), outcome = c(2.3, 1.9, 3.2, 1))

ggplot(df) +
  geom_col_pattern(
    aes(level, outcome, pattern_fill = level), 
    pattern = 'stripe',
    fill    = 'white',
    colour  = 'black'
  ) +
  theme_bw(18) +
  theme(legend.position = 'none') + 
  labs(
    title    = "ggpattern::geom_col_pattern()",
    subtitle = "pattern = 'stripe'"
  ) +
  coord_fixed(ratio = 1/2)

Gallery

Feature Details

Available Geoms

ggpattern includes versions of (nearly) all geoms from ggplot2 which could plausibly support being filled with a pattern.

See the vignette galleries for examples of all the available geoms filled with geometry-based patterns and image-based/array-based patterns.

Click to show/hide list of supported geoms
ggplot2 ggpattern
geom_area geom_area_pattern
geom_bar geom_bar_pattern
geom_bin2d geom_bin2d_pattern
geom_boxplot geom_boxplot_pattern
geom_col geom_col_pattern
geom_crossbar geom_crossbar_pattern
geom_density geom_density_pattern
geom_histogram geom_histogram_pattern
geom_map geom_map_pattern
geom_polygon geom_polygon_pattern
geom_rect geom_rect_pattern
geom_ribbon geom_ribbon_pattern
geom_sf geom_sf_pattern
geom_tile geom_tile_pattern
geom_violin geom_violin_pattern

New aesthetics

To control pattern appearance, a raft of new aesthetics have been added. e.g. pattern_alpha, pattern_filename, pattern_density.

There are also scale functions to control each of these new aesthetics e.g. scale_pattern_alpha_discrete.

Not all aesthetics apply to all patterns. See the individual pattern vignettes for which aesthetics it uses, or see the first vignette on developing user-defined patterns for a table of aesthetic use by pattern, or see the individual vignettes for each pattern.

Click to show/hide list of new aesthetics
aesthetic description default possible values
pattern Name of the pattern to draw 'stripe' stripe, crosshatch, circle, image, placeholder, magick, gradient, plasma
pattern_type Generic control option NA pattern-dependent
pattern_subtype Generic control option NA pattern-dependent
pattern_alpha Alpha 1 value in range [0, 1] (npc units)
pattern_linetype Stroke linetype 1 linetype
pattern_size Stroke linewidth 1 linewidth
pattern_shape Plotting shape 1 shapes
pattern_colour Stroke colour 'grey20' colour
pattern_fill Fill colour 'grey80' colour
pattern_fill2 Second fill colour '#4169E1' colour
pattern_angle Rotation angle 30 angle in degrees
pattern_density Approx. fraction of area the pattern fills 0.2 value in range [0, 1] (fraction)
pattern_spacing Spacing between repetitions of pattern 0.05 value in range [0, 1] (npc units)
pattern_xoffset Shift pattern along x axis 0 value in range [0, 1] (npc units)
pattern_yoffset Shift pattern along y axis 0 value in range [0, 1] (npc units)
pattern_aspect_ratio Aspect ratio adjustment NA usual range [0.01, 10]
pattern_key_scale_factor Scale factor for pattern in legend 1
pattern_filename Image filename/URL '' Filename/URL
pattern_gravity Image placement 'center' ggpattern::magick_gravity_names
pattern_filter Image scaling filter 'lanczos' ggpattern::magick_filter_names
pattern_scale Scale 1 Multiplier
pattern_orientation Orientation 'vertical' 'vertical', 'horizontal', 'radial'
pattern_phase Phase 0
pattern_frequency Frequency 0.1
pattern_option_1 - 5 Generic options for expansion 0
pattern_grid Grid type 'square' 'square', 'hex', 'hex_circle'
pattern_res Pattern resolution (pixels per inch) NA Resolution
pattern_rot Shape rotation angle (within pattern) 0 angle in degrees

User-Defined Patterns

Users can write their own pattern functions and ask ggpattern to use them, without having to include the pattern in the package.

See the vignette on developing patterns: vignette("developing-patterns", package = "ggpattern").

Vignettes

Note: due to CRAN package size limits many of these vignettes are only available in the Github version of {ggpattern} and the package website.

General examples

Exploration of pattern parameters and appearance

Developing your own pattern

Other examples

Limitations

  • Use pattern_aspect_ratio to override the internal aspect ratio calculation.
  • Legend rendering for patterns is still not great.
    • Use pattern_key_scale_factor to adjust legend appearance.
  • The Rstudio output device can be quite slow for plots with lots of patterns. It is often faster to save directly to PNG or PDF and view that.
  • Self intersecting geometry can be an issue.
  • Non-linear coordinate systems have not been tested.