Extending ggplot2: How to build a geom and stat? - r

Question

I am in the early stages of learning how to extend ggplot2. I would like to create a custom geom and associated stat. My starting point was the vignette. In addition, I have benefited from this and this. I'm trying to put together a template to teach myself and hopefully others.
Main question:
Inside my function calculate_shadows() the needed parameter params$anchor is NULL. How can I access it?
The goal described below is intended solely for learning how to create custom stat and geom functions, it's not a real goal: as you can see from the screenshots, I do know how to leverage the power of ggplot2 to make the graphs.
The geom will read the data and for the supplied variables ("x", "y") will plot (for want of a better word) shadows: a horizontal line min(x)--max(x) at the default y=0 and a vertical line min(y)--max(y) at the default x=0. If an option is supplied, these "anchors" could be changed, e.g. if the user supplies x = 35, y = 1, the horizontal line would be drawn at the intercept y = 1 while the vertical line would be drawn at the intercept x = 35. Usage:
library(ggplot2)
ggplot(data = mtcars, aes(x = mpg, y = wt)) +
geom_point() +
geom_shadows(x = 35, y = 1)
The stat will read the data and for the supplied variables ("x", "y") will compute shadows according to the value of stat. For instance, by passing stat = "identity", the shadows would be computed for the min and max of the data (as done by geom_shadows). But by passing stat = "quartile", the shadows would be computed for first and third quartile. More generally, one could pass a function like stats::quantile with arguments args = list(probs = c(0.10, 0.90), type = 6), to compute shadows using the 10th and 90th percentiles and the quantile method of type 6. Usage:
ggplot(data = mtcars, aes(x = mpg, y = wt)) +
geom_point() +
stat_shadows(stat = "quartile")
Unfortunately, my lack of familiarity with extending ggplot2 stopped me well short of my objective. These plots were "faked" with geom_segment. Based on the tutorial and discussions cited above and inspecting existing code like stat-qq or stat-smooth, I have put together a basic architecture for this goal. It must contain many mistakes, I would be grateful for guidance. Also, note that either of these approaches would be fine: geom_shadows(anchor = c(35, 1)) or geom_shadows(x = 35, y = 1).
Now here are my efforts. First, geom-shadows.r to define geom_shadows(). Second, stat-shadows.r to define stat_shadows(). The code doesn't work as is. But if I execute its content, it does produce the desired statistics. For clarity, I have removed most of the calculations in stat_shadows(), such as quartiles, to focus on essentials. Any obvious mistake in the layout?
geom-shadows.r
#' documentation ought to be here
geom_shadows <- function(
mapping = NULL,
data = NULL,
stat = "shadows",
position = "identity",
...,
anchor = list(x = 0, y = 0),
shadows = list("x", "y"),
type = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomShadows,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
anchor = anchor,
shadows = shadows,
type = type,
na.rm = na.rm,
...
)
)
}
GeomShadows <- ggproto("GeomShadows", Geom,
# set up the data, e.g. remove missing data
setup_data = function(data, params) {
data
},
# set up the parameters, e.g. supply warnings for incorrect input
setup_params = function(data, params) {
params
},
draw_group = function(data, panel_params, coord, anchor, shadows, type) {
# draw_group uses stats returned by compute_group
# set common aesthetics
geom_aes <- list(
alpha = data$alpha,
colour = data$color,
size = data$size,
linetype = data$linetype,
fill = alpha(data$fill, data$alpha),
group = data$group
)
# merge aesthetics with data calculated in setup_data
geom_stats <- new_data_frame(c(list(
x = c(data$x.xmin, data$y.xmin),
xend = c(data$x.xmax, data$y.xmax),
y = c(data$x.ymin, data$y.ymin),
yend = c(data$x.ymax, data$y.ymax),
alpha = c(data$alpha, data$alpha)
), geom_aes
), n = 2)
# turn the stats data into a GeomPath
geom_grob <- GeomSegment$draw_panel(unique(geom_stats),
panel_params, coord)
# pass the GeomPath to grobTree
ggname("geom_shadows", grobTree(geom_grob))
},
# set legend box styles
draw_key = draw_key_path,
# set default aesthetics
default_aes = aes(
colour = "blue",
fill = "red",
size = 1,
linetype = 1,
alpha = 1
)
)
stat-shadows.r
#' documentation ought to be here
stat_shadows <-
function(mapping = NULL,
data = NULL,
geom = "shadows",
position = "identity",
...,
# do I need to add the geom_shadows arguments here?
anchor = list(x = 0, y = 0),
shadows = list("x", "y"),
type = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
stat = StatShadows,
data = data,
mapping = mapping,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
# geom_shadows argument repeated here?
anchor = anchor,
shadows = shadows,
type = type,
na.rm = na.rm,
...
)
)
}
StatShadows <-
ggproto("StatShadows", Stat,
# do I need to repeat required_aes?
required_aes = c("x", "y"),
# set up the data, e.g. remove missing data
setup_data = function(data, params) {
data
},
# set up parameters, e.g. unpack from list
setup_params = function(data, params) {
params
},
# calculate shadows: returns data_frame with colnames: xmin, xmax, ymin, ymax
compute_group = function(data, scales, anchor = list(x = 0, y = 0), shadows = list("x", "y"), type = NULL, na.rm = TRUE) {
.compute_shadows(data = data, anchor = anchor, shadows = shadows, type = type)
}
)
# Calculate the shadows for each type / shadows / anchor
.compute_shadows <- function(data, anchor, shadows, type) {
# Deleted all type-checking, etc. for MWE
# Only 'type = c(double, double)' accepted, e.g. type = c(0, 1)
qs <- type
# compute shadows along the x-axis
if (any(shadows == "x")) {
shadows.x <- c(
xmin = as.numeric(stats::quantile(data[, "x"], qs[[1]])),
xmax = as.numeric(stats::quantile(data[, "x"], qs[[2]])),
ymin = anchor[["y"]],
ymax = anchor[["y"]])
}
# compute shadows along the y-axis
if (any(shadows == "y")) {
shadows.y <- c(
xmin = anchor[["x"]],
xmax = anchor[["x"]],
ymin = as.numeric(stats::quantile(data[, "y"], qs[[1]])),
ymax = as.numeric(stats::quantile(data[, "y"], qs[[2]])))
}
# store shadows in one data_frame
stats <- new_data_frame(c(x = shadows.x, y = shadows.y))
# return the statistics
stats
}
.

Answer 1

Until a more thorough answer comes along: You are missing
extra_params = c("na.rm", "shadows", "anchor", "type"),
inside GeomShadows <- ggproto("GeomShadows", Geom,
and possibly also inside StatShadows <- ggproto("StatShadows", Stat,.
Inside geom-.r and stat-.r there are many very useful comments that clarify how geoms and stats work. In particular (hat tips Claus Wilke over at github issues):
# Most parameters for the geom are taken automatically from draw_panel() or
# draw_groups(). However, some additional parameters may be needed
# for setup_data() or handle_na(). These can not be imputed automatically,
# so the slightly hacky "extra_params" field is used instead. By
# default it contains `na.rm`
extra_params = c("na.rm"),