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.
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:
- Have the exact function signature:
function(params, boundary_df, aspect_ratio, legend)
params - parameters from the geom (the aesthetics) e.g pattern_fillboundary_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.
- 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$pattern_size)
grid::polygonGrob(x = x, y = y, id = id, default.units = "npc", gp = gp)
}
A global option ggpattern_geometry_funcs is a named list which contains geometry-based pattern creating functions to use outside of ggpattern.
The name used in this list corresponds to the pattern name used with the geom - in this case we will be using pattern = 'polygon'.
options(ggpattern_geometry_funcs = list(polygon = create_pattern_polygon))
grid.pattern("polygon", fill = "red", size = 4, linetype = "dashed",
x = c(0.05, 0.05, 0.305, 0.305), y = c(0.05, 0.305, 0.305, 0.05))
grid.pattern("polygon", fill = "green", alpha = 0.2,
x = c(0.35, 0.35, 0.65, 0.65), y = c(0.35, 0.65, 0.65, 0.35))
grid.pattern("polygon", fill = "blue", colour = "grey",
x = c(0.7, 0.7, 1.0, 1.0), y = c(0.7, 1.0, 1.0, 0.7))
Example geometry-based pattern function #2 (using other patterns)
All geometry-based pattern creation functions must:
- Have the exact function signature:
function(params, boundary_df, aspect_ratio, legend)
params - parameters from the geom (the aesthetics) e.g pattern_fillboundary_df - data.frame containing polygon information i.e. The polygon_df format.aspect_ratio - the best guess that {gridpattern} / {ggpattern} is able to make as to the aspect ratio of the viewport in which this pattern is being rendered.legend logical value to indicate whether or not this function is being called to render a key legend or the in-place geom fill.
- Return a grid grob bounded by the boundary represented by
boundary_df (including grid structures like a grid::grobTree()).
For this example we’ll create an example that re-uses the pre-existing ‘stripe’, ‘circle’, and ‘gradient’ patterns and combines them into a new ‘complex’ pattern.
create_pattern_complex <- function(params, boundary_df, aspect_ratio, legend = FALSE) {
args <- as.list(params)
args <- args[grep("^pattern_", names(args))]
args$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:
- Have the exact function signature:
function(width, height, params, legend)
width,height - dimensions of the bounding box of the geom areaparams - parameters from the geom (the aesthetics) e.g pattern_filllegend logical value to indicate whether or not this function is being called to render a key legend or the in-place geom fill.
- 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))
