Developing Patterns

library("ggplot2")
library("ggpattern")

Developing Patterns - overview

To develop a pattern for use with ggpattern (and any other packages that use gridpattern) you will need to:

1. Decide whether this is a geometry-based pattern or an array-based pattern.
2. Create a function with the required arguments and return value
3. Use options() to let gridpattern know that a certain pattern name should be delegated to your function.

This vignette shows how to:

• write a create_pattern() function of the correct signature for a geometry-based pattern or array-based pattern
• Instruct ggpattern on where to find this user-defined pattern

Table of Contents

• The two pattern classes
• List of all pattern aesthetics
• Aesthetic use by {ggpattern} patterns
• Geometry-based pattern functions
• Array-based pattern functions
• Example: Three-color polygon tilings (adapting {ggplot2} aesthetics)
• Other examples

Pattern Classification - geometry-based and array-based

There are only 2 high-level classes of pattern supported by gridpattern - geometry-based and array-based.

Geometry-based patterns create a series of geometry objects and trim them (using sf::st_intersection(), gridGeometry::polyclipGrob(), gridpattern::alphaMaskGrob(), etc) to be within the boundary of the grob. For example, the ‘stripes’ pattern in gridpattern is a series of equally spaced rectangular polygons.

Array-based patterns are RGBA image arrays. Any supplied image will be processed by gridpattern to ensure it is masked to only apply to the area within the grob’s boundary.

{ggpattern} Aesthetics - Descriptions and Defaults

Although custom gridpattern pattern parameters need not limit itself to the set of aesthetics provided by ggpattern doing so may make your pattern more useful for others:

{ggpattern} aesthetic summary - click to open/close

aesthetic	description	default	possible values
pattern	Name of the pattern to draw	‘stripe’	gridpattern::names_pattern
pattern_alpha	Alpha	1	value in range [0, 1] or NA
pattern_angle	Rotation angle (entire pattern)	30	angle in degrees
pattern_aspect_ratio	Aspect ratio adjustment	NA	usual range [0.01, 10]
pattern_colour	Stroke colour	‘grey20’	colour
pattern_density	Approx. fraction of area the pattern fills	0.2	value in range [0, 1]
pattern_filename	Image filename/URL	’’	Filename/URL
pattern_fill	Fill colour	‘grey80’	colour (or grid pattern/gradient)
pattern_fill2	Second fill colour	‘#4169E1’	colour (or grid pattern/gradient)
pattern_filter	Image scaling filter	‘lanczos’	magick::filter_types
pattern_frequency	Frequency	0.1
pattern_gravity	Image placement	‘center’	magick::gravity_types
pattern_grid	Pattern grid type	‘square’	‘square’, ‘hex’, ‘hex_circle’
pattern_key_scale_factor	Scale factor for pattern in legend	1
pattern_linetype	Stroke linetype	1	linetype
pattern_option_1 - 5	Generic options for expansion	0
pattern_orientation	Orientation	‘vertical’	‘vertical’, ‘horizontal’, ‘radial’
pattern_phase	Phase	0
pattern_res	Pattern resolution (pixels per inch)	NA
pattern_rot	Rotation angle (shape within pattern)	0	angle in degrees
pattern_scale	Scale	1	Multiplier
pattern_shape	Plotting shape	1	shapes
pattern_size	Stroke linewidth	1	linewidth
pattern_spacing	Spacing between repetitions of pattern	0.05	value in pattern_units grid units
pattern_subtype	Generic control option	NA	pattern-dependent
pattern_type	Generic control option	NA	pattern-dependent
pattern_units	Pattern grid unit	‘snpc’	grid::unit() unit i.e. ‘snpc’, ‘cm’, and ‘inches’
pattern_xoffset	Shift pattern along x axis	0	value in pattern_units grid units
pattern_yoffset	Shift pattern along y axis	0	value in pattern_units grid units

Note ggpattern may also pass other geom aesthetics of possible interest such as fill. Also note that ggpattern will only pass pattern aesthetics values of length one but if the pattern is called directly by gridpattern::patternGrob() then the pattern may be passed pattern parameters of arbitrary length.

Geometry-based pattern functions - Formal Arguments and Return Values

All geometry-based pattern creation functions must:

1. Have the exact function signature: function(params, boundary_df, aspect_ratio, legend)

   • params - parameters for the pattern (the aesthetics) e.g pattern_fill
   • boundary_df - data.frame containing polygon information i.e. The polygon_df format.
   • aspect_ratio - the best guess that gridpattern / ggpattern is able to make as to the aspect ratio of the viewport in which this pattern is being rendered.
   • legend logical value to indicate whether or not this function is being called to render a key legend or the in-place geom fill.

2. Return a grid grob object. This can be any valid grob including a grid::grobTree(). The user should make sure it lies within the boundary represented by boundary_df either by clipping with functions like sf::st_intersection(), gridGeometry::polyclipGrob(), gridpattern::alphaMaskGrob(), etc. or using bounded grob functions like gridpattern::patternGrob() or grid::polygonGrob().

Array-based pattern functions - Formal Arguments and Return Values

All array-based pattern creation functions must:

1. Have the exact function signature: function(width, height, params, legend)
   • width,height - dimensions of the bounding box of the geom area
   • params - parameters from the geom (the aesthetics) e.g pattern_fill
   • legend logical value to indicate whether or not this function is being called to render a key legend or the in-place geom fill.
2. Return a 3D array of RGBA values (all values in the range [0, 1]). gridpattern itself will mask this image so that it only applies to the area within the grob’s boundary.

The polygon_df data.frame format

The polygon_df is a very simple data.frame format to contain polygon values. This is used to pass the coordinates of the geom boundary from the geom to the pattern generating function.

It contains only ‘x’ and ‘y’ columns for the coordinates, and an ‘id’ column used to signify which polygon the coordinates belong to.

The following polygon_df data.frame contains 2 polygons:

example data in ‘polygon_df’ format

x	y	id
0	0	1
1	0	1
1	1	1
0	1	1
0	0	2
2	0	2
2	1	2
0	1	2

Associating a function with {gridpattern} pattern name

There are two global option() values which can be set - one for geometry-based patterns, and the other for array-based patterns.

The global values should point to a named list, where the names are the pattern names you want to use within gridpattern, and the named values are the actual functions. Note for backwards-compatibility with the original ggpattern system these options start with ggpattern instead of gridpattern.

options(ggpattern_array_funcs    = list(your_pattern_name = your_pattern_function))
options(ggpattern_geometry_funcs = list(your_pattern_name = your_pattern_function))

Pattern names must be different from any of the builtin patterns included in gridpattern.

Example: Three-color polygon tilings (adapting {ggplot2} aesthetics)

All geometry-based pattern creation functions must:

1. Have the exact function signature: function(params, boundary_df, aspect_ratio, legend)
   • params - parameters from the geom (the aesthetics) e.g pattern_fill
   • boundary_df - data.frame containing polygon information i.e. The polygon_df format.
   • aspect_ratio - the best guess that gridpattern / ggpattern is able to make as to the aspect ratio of the viewport in which this pattern is being rendered.
   • legend logical value to indicate whether or not this function is being called to render a key legend or the in-place geom fill.
2. Return a grid grob bounded by the boundary represented by boundary_df (including grid structures like a grid::grobTree()).

For this example we’ll adapt the built-in ‘polygon_tiling’ pattern to create a new ‘tiling3’ pattern that fills the polygon tiling with three colors: the fill aesthetic, the pattern_fill aesthetic, and their “average” color.

tiling3_pattern <- function(params, boundary_df, aspect_ratio, legend = FALSE) {
    args <- as.list(params)
    args <- args[grep("^pattern_", names(args))]

    # hexagonal tiling using "regular_polygon" pattern
    args$pattern <- "polygon_tiling"

    # three-color tiling using `fill`, `pattern_fill` and their "average"
    avg_col <- gridpattern::mean_col(params$fill, params$pattern_fill)
    args$pattern_fill <- c(params$fill, avg_col, args$pattern_fill)

    args$x <- boundary_df$x
    args$y <- boundary_df$y
    args$id <- boundary_df$id
    args$prefix <- ""

    do.call(gridpattern::patternGrob, args)
}

A global option ggpattern_geometry_funcs is a named list which contains geometry-based pattern creating functions to use outside of ggpattern.

The name used in this list corresponds to the pattern name used with the geom - in this case we will be using pattern = 'complex'.

options(ggpattern_geometry_funcs = list(tiling3 = tiling3_pattern))

df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2))
ggplot(df, aes(trt, outcome)) +
    geom_col_pattern(aes(fill = trt, pattern_type = trt),
                     pattern = 'tiling3',
                     pattern_angle = 45,
                     pattern_spacing = 0.15) +
    scale_pattern_type_manual(values = c("hexagonal", "tetrakis_square", "rhombille")) +
    theme(legend.key.size = unit(1.2, 'cm'))

Other examples

The gridpattern package contains a vignette on developing gridpattern / ggpattern patterns with a few more examples including an example of layering patterns on top of each other. Use vignette("developing-patterns", package="gridpattern") to see it.

Also the gridpattern source contains the full source code for 19patterns: https://github.com/trevorld/gridpattern/tree/main/R