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 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 gridpattern on where to find this user-defined pattern

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_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 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

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 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_size)

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

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 = 'polygon'.

options(ggpattern_geometry_funcs = list(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$pattern <- "stripe"
    args_stripe$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$pattern <- "regular_polygon"
    args_circle$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$pattern <- "gradient"
    args_gradient$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)
}

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(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
}

A global option ggpattern_array_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 = 'simple'.

options(ggpattern_array_funcs = list(simple = create_pattern_simple))
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 seventeen patterns: https://github.com/trevorld/gridpattern/tree/main/R