Developing Patterns

library("gridpattern")

Developing Patterns - overview

To develop a pattern for use with gridpattern (and packages that use it such as ggpattern) 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 register_pattern() 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 gridpattern 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
• Geometry-based example #1 (recreate polygon)
• Geometry-based example #2 (using other patterns)
• Array-based example
• 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::clippingPathGrob(), 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_fill2	Second fill colour	‘#4169E1’	colour
pattern_fill	Fill colour	‘grey80’	colour
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_linewidth	Stroke linewidth	1	linewidth
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	Size factor (e.g. fontsize)	1	fontsize
pattern_spacing	Spacing between repetitions of pattern	0.05	value in range [0, 1] (snpc units)
pattern_subtype	Generic control option	NA	pattern-dependent
pattern_type	Generic control option	NA	pattern-dependent
pattern_xoffset	Shift pattern along x axis	0	value in range [0, 1] (snpc units)
pattern_yoffset	Shift pattern along y axis	0	value in range [0, 1] (snpc 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::clippingPathGrob(), 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

Use register_pattern() to associate a pattern function with a pattern name. Use kind = "geometry" (the default) for geometry-based patterns and kind = "array" for array-based patterns.

register_pattern("your_pattern_name", your_geometry_pattern_function)
register_pattern("your_pattern_name", your_array_pattern_function, kind = "array")

• Packages should register their patterns in their .onLoad() function (see Registering patterns from a package below).
• Patterns can always be referred to by their qualified name "owner::name" e.g. "pkg::name", "gridpattern::stripe", or "R_GlobalEnv::name" (for patterns registered by the user).
• A bare name "name" may be used if only one owner (the user, gridpattern, or a package) has a pattern with that name. Otherwise there is a conflict and using the bare name throws an error unless the user has declared a preference with prefer_pattern() e.g. prefer_pattern("R_GlobalEnv::stripe") to use a user’s custom “stripe” pattern instead of the builtin one.
• conflicting_patterns() lists patterns whose bare names are shared by more than one pattern. unprefer_pattern() removes a preference.
• Package code that relies on a particular pattern should use its qualified name.
• register_pattern()’s defaults argument may set pattern-specific default parameter values e.g. defaults = list(type = "running", spacing = 0.1). Note ggpattern supplies its own defaults for most of its pattern aesthetics.
• registered_patterns() lists all the available patterns and unregister_pattern() removes a registration.
• has_pattern() checks whether pattern names currently resolve to a pattern.
• local_pattern() registers a pattern only until the current function (or test) exits.

Registering patterns from a package

We recommend packages register their patterns in their .onLoad() function using rlang::on_package_load():

.onLoad <- function(libname, pkgname) {
    rlang::on_package_load("gridpattern", {
        if (exists("register_pattern", envir = asNamespace("gridpattern"), inherits = FALSE)) {
            gridpattern::register_pattern("brick", create_pattern_brick)
        } else {
            funcs <- getOption("ggpattern_geometry_funcs", list())
            funcs[["brick"]] <- create_pattern_brick
            options(ggpattern_geometry_funcs = funcs)
        }
    })
}

• rlang::on_package_load() registers the pattern immediately if gridpattern is already loaded and otherwise when gridpattern is later loaded. This means gridpattern may be listed in Suggests (rather than Imports) and gridpattern won’t be loaded until needed.

• It also re-registers the pattern if gridpattern is reloaded (e.g. by devtools::load_all()) which would otherwise forget the package’s patterns.

• Your package is still detected as the owner of the pattern so it may be referred to as "yourpkg::brick".

• If writing a helper function that calls register_pattern() on behalf of your package pass along register_pattern()’s env argument.

• register_pattern() was added in gridpattern v1.5.0. The exists("register_pattern", ...) check above detects whether gridpattern is too old and the else clause falls back to appending the pattern to the legacy global options, preserving any other custom patterns already set there. Use the ggpattern_array_funcs option instead for array-based patterns. Note this modifies the user’s global options when your package is loaded.

Example geometry-based pattern #1 (recreate polygon)

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 create a simple single color fill pattern based on grid::polygonGrob() called ‘polygon’.

create_pattern_polygon <- function(params, boundary_df, aspect_ratio, legend = FALSE) {
    x <- boundary_df$x
    y <- boundary_df$y
    id <- boundary_df$id

    alpha <- ifelse(is.na(params$pattern_alpha), 1, params$pattern_alpha)
    gp <- grid::gpar(alpha = alpha,
                     col = params$pattern_colour,
                     fill = params$pattern_fill,
                     lty = params$pattern_linetype,
                     lwd = params$pattern_linewidth)

    grid::polygonGrob(x = x, y = y, id = id, default.units = "npc", gp = gp)
}

We register the function with register_pattern(). The name corresponds to the pattern name used with grid.pattern() or the geom - in this case we will be using pattern = 'polygon'.

register_pattern("polygon", create_pattern_polygon)

grid.pattern("polygon", fill = "red", size = 4, linetype = "dashed",
             x = c(0.05, 0.05, 0.305, 0.305), y = c(0.05, 0.305, 0.305, 0.05))
grid.pattern("polygon", fill = "green", alpha = 0.2,
             x = c(0.35, 0.35, 0.65, 0.65), y = c(0.35, 0.65, 0.65, 0.35))
grid.pattern("polygon", fill = "blue", colour = "grey",
             x = c(0.7, 0.7, 1.0, 1.0), y = c(0.7, 1.0, 1.0, 0.7))

Example geometry-based pattern function #2 (using other patterns)

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 create an example that re-uses the pre-existing ‘stripe’, ‘circle’, and ‘gradient’ patterns and combines them into a new ‘complex’ pattern.

create_pattern_complex <- function(params, boundary_df, aspect_ratio, legend = FALSE) {
    args <- as.list(params)
    args <- args[grep("^pattern_", names(args))]
    args$x <- boundary_df$x
    args$y <- boundary_df$y
    args$id <- boundary_df$id
    args$prefix <- ""

    args_stripe <- args
    args_stripe$pattern <- "gridpattern::stripe"
    args_stripe$pattern_density <- 0.5 * args$pattern_density
    args_stripe$pattern_spacing <- 2 * args$pattern_spacing
    grob_stripe <- do.call(gridpattern::patternGrob, args_stripe)

    args_circle <- args
    args_circle$pattern <- "gridpattern::regular_polygon"
    args_circle$pattern_shape <- c("circle", "null")
    args_circle$pattern_yoffset <- args$pattern_spacing + args$pattern_yoffset
    args_circle$pattern_type = "horizontal"
    grob_circle <- do.call(gridpattern::patternGrob, args_circle)

    args_gradient <- args
    args_gradient$pattern <- "gridpattern::gradient"
    args_gradient$pattern_fill <- "#00000070"
    args_gradient$pattern_fill2 <- "#FFFFFF70"
    args_gradient$pattern_orientation <- "vertical"
    grob_gradient <- do.call(gridpattern::patternGrob, args_gradient)

    grid::grobTree(grob_stripe, grob_circle, grob_gradient)
}

We register the function with register_pattern(). The name corresponds to the pattern name used with grid.pattern() or the geom - in this case we will be using pattern = 'complex'.

register_pattern("complex", create_pattern_complex)

grid.pattern("complex", fill = "red", angle = 45, spacing = 0.05, density = 0.3,
             x = c(0.0, 0.0, 0.3, 0.3), y = c(0.0, 0.3, 0.3, 0.0))
grid.pattern("complex", fill = "green", angle = 45, spacing = 0.2, density = 0.2,
             x = c(0.35, 0.35, 0.65, 0.65), y = c(0.35, 0.65, 0.65, 0.35))
grid.pattern("complex", fill = "blue", angle = 45, spacing = 0.1, density = 0.3,
             x = c(0.7, 0.7, 1.0, 1.0), y = c(0.7, 1.0, 1.0, 0.7))
grid::grid.polygon(x = c(0.0, 0.0, 0.3, 0.3, 0.35, 0.35, 0.65, 0.65, 0.7, 0.7, 1.0, 1.0),
                   y = c(0.0, 0.3, 0.3, 0.0, 0.35, 0.65, 0.65, 0.35, 0.7, 1.0, 1.0, 0.7),
                   id = rep(1:3, each = 4),
                   gp = grid::gpar(col = "black", fill = NA, lwd=4))

Example array-based pattern function

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]).

For this example we’ll create a simple example that cycles through RGBA values.

Parameters for this pattern:

• pattern_type is used to distinguish between source data for the pattern

Note: This pattern exploits vector recyling in the creation of the RGBA array, and as dimensions change the alignment of the R, G, B and A planes will not remain in a fixed relationship. Thus if you change the shape of the rendered image, you will change the nature of the pattern.

create_pattern_simple <- function(width, height, params, legend) {

  # Ensure the selected pattern is sane.
  choice <- params$pattern_type
  if (is.null(choice) || is.na(choice) || !is.character(choice)) {
    choice <- 'a'
  }

  # Choose the values with which to fill the array
  values <- switch(
    choice,
    a = rep(c(0, 1, 0, 1, 1, 0, 0, 1, 1, 1), each = 3),
    b = rep(c(1, 0, 0, 1, 0.5, 0.5, 1, 1, 0, 0, 0, 0, 0, 0.5), each = 7),
    c = rep(seq(0, 1, 0.05), each = 7),
    rep(c(0, 1, 0, 1, 1, 0, 0, 1, 1, 1), each = 3)
  )
  # Create an RGBA array of the requested dimensions
  simple_array <- array(values, dim = c(height, width, 4))

  simple_array
}

We register the function with register_pattern() using kind = "array". The name corresponds to the pattern name used with grid.pattern() or the geom - in this case we will be using pattern = 'simple'.

register_pattern("simple", create_pattern_simple, kind = "array")

grid::grid.polygon(x = c(0, 0, 1, 1), y = c(0, 1, 1, 0),
                   gp = grid::gpar(col=NA, fill="grey"))
grid.pattern("simple", type = "a",
             x = c(0.0, 0.0, 0.3, 0.3), y = c(0.0, 0.3, 0.3, 0.0))
grid.pattern("simple", type = "b",
             x = c(0.35, 0.35, 0.65, 0.65), y = c(0.35, 0.65, 0.65, 0.35))
grid.pattern("simple", type = "c",
             x = c(0.7, 0.7, 1.0, 1.0), y = c(0.7, 1.0, 1.0, 0.7))

Other examples

The ggpattern package contains a vignette on developing gridpattern / ggpattern patterns with a few more examples: https://coolbutuseless.github.io/package/ggpattern/articles/

Also the gridpattern source contains the full source code for 21 patterns: https://github.com/trevorld/gridpattern/tree/main/R