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Add Bubble Glyphs as a Scatterplot

Source: R/geom_bubbleglyph.R
geom_bubbleglyph.Rd

The bubbleglyph geom is used to plot multivariate data as bubble glyphs in a scatterplot. Each variable specified in cols is depicted as a circle, with the radius (or area) scaled according to the corresponding value.

Usage

geom_bubbleglyph(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  cols = character(0L),
  scale.radius = TRUE,
  scale.area = FALSE,
  bubble.layout = c("annulus", "circle", "line", "chain", "hub", "pack"),
  connector = c("none", "foreground", "background"),
  fill.bubble = NULL,
  fill.gradient = NULL,
  colour.bubble = NULL,
  colour.grid = NULL,
  linewidth = 1,
  linewidth.grid = linewidth,
  linejoin = c("mitre", "round", "bevel"),
  angle.start = 0,
  angle.stop = 2 * base::pi,
  draw.grid = FALSE,
  legend.glyph.dims = setNames(rep(0.5, length(cols)), cols),
  show.legend = NA,
  repel = FALSE,
  repel.control = ggmultiglyph.repel.control(),
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

The statistical transformation to use on the data for this layer. When using a geom_*() function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "green" or size = 3. They may also be parameters to the paired geom/stat.

cols

A character vector containing the names of at least two columns specifying the variables to be plotted in the glyphs. The selected columns must be either numeric or factor variables.

scale.radius

logical. If TRUE, the values in z are used directly as the bubble radii.

scale.area

logical. If TRUE, values in z are treated as bubble areas, and radii are derived as \(\sqrt{z}\), so that bubble area (rather than radius) is proportional to z.

bubble.layout

The layout algorithm used to position the bubbles. One of "circle", "line", "chain", "hub", "pack" or "annulus" (See Layouts for more details).

connector

The style used to connect bubbles to one another. One of "none" (no connectors are drawn), "foreground" (connectors are drawn on top of the bubbles) or "background" (connectors are drawn underneath the bubbles).

fill.bubble

The fill colour of the bubbles.

fill.gradient

The palette for gradient fill of the segments. See Details section of col_numeric() function in the scales package for available options.

colour.bubble

The colour of bubbles.

colour.grid

The colour of grid lines.

linewidth

The line width of the circles.

linewidth.grid

The line width of the grid circles.

linejoin

The line join style for the tile polygon. Either "mitre", "round" or "bevel".

angle.start

The start angle for the bubbles in radians for layout = "circle" and layout = "hub". Default is zero.

angle.stop

The stop angle for the bubbles in radians for layout = "circle" and layout = "hub". Default is \(2\pi\).

draw.grid

logical. If TRUE, grid levels are plotted as nested circles within each bubble. Default is FALSE.

legend.glyph.dims

The dimensions of the legend glyph plot. Can be a numeric vector of unit length (where all the dimensions will have same value) or a numeric vector of same length as "cols" with the "cols" as names.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

repel

logical. If TRUE, the glyphs are repel away from each other to avoid overlaps. Default is FALSE.

repel.control

A list of control settings for the repel algorithm. Ignored if repel = FALSE. See ggmultiglyph.repel.control for details on the various control parameters.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().

Value

A geom layer.

Aesthetics

geom_bubbleglyph() understands the following aesthetics (required aesthetics are in bold):

  • x

  • y

  • alpha

  • colour

  • fill

  • group

  • size

  • centre.size

See vignette("ggplot2-specs", package = "ggplot2") for further details on setting these aesthetics.

The following additional aesthetics are considered if repel = TRUE:

  • point.size

  • segment.linetype

  • segment.colour

  • segment.size

  • segment.alpha

  • segment.curvature

  • segment.angle

  • segment.ncp

  • segment.shape

  • segment.square

  • segment.squareShape

  • segment.inflect

  • segment.debug

See ggrepel examples page for further details on setting these aesthetics.

Layouts

The following layouts are available.

"circle"

Bubbles are arranged around the circumference of an invisible circle, evenly spaced by angle between angle.start and angle.stop. The radius of this invisible circle is derived from the bubble radii (the largest bubble radius plus the mean bubble radius, with a small buffer added) so that bubbles do not overlap regardless of their individual sizes. This is the default layout.

"line"

Bubbles are arranged side by side along a straight line passing through the glyph centre, each bubble touching its neighbours. The line may be rotated to any orientation using the line.angle argument (in radians).

"chain"

Bubbles are linked together in a meandering tangent chain. Each new bubble is placed tangent to its immediate predecessor, alternating between opposite sides of the chain to produce a distinctive zig-zag arrangement. Where necessary, the placement is adjusted to minimise overlap with previously placed bubbles while preserving the ordering of the data.

"hub"

One bubble (the one with the largest radius) is treated as a central "hub", and all other bubbles are placed around it, each touching the hub bubble, at angles spaced between angle.start and angle.stop. This is a quick, deterministic layout: because the surrounding bubbles are not tested against one another for overlap, bubbles can overlap when several of them are large relative to the hub.

"pack"

Bubbles are arranged using a circle-packing algorithm (circleProgressiveLayout), which places bubbles as close together as possible without any overlap (Collins and Stephenson 2003; Wang et al. 2006; Bedward et al. 2024) . This produces the most compact, space-efficient arrangement of the available layouts, at the cost of the arrangement having no inherent order or direction (bubbles are not ordered along an axis or around a hub).

"annulus"

Bubbles are arranged, in the order supplied, around the circumference of a ring (annulus), with each bubble touching its immediate neighbours on either side (the last bubble touching the first, closing the ring). The radius of the ring is solved numerically so that all adjacent bubbles are mutually tangent.

References

Bedward M, Eppstein D, Menzel P (2024). “packcircles: Circle Packing. R package version 0.3.7.”

Collins CR, Stephenson K (2003). “A circle packing algorithm.” Computational Geometry, 25(3), 233–256.

Wang W, Wang H, Dai G, Wang H (2006). “Visualization of large hierarchical data by circle packing.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 517–520. ISBN 978-1-59593-372-0.

See also

bubbleglyphGrob

Other geoms: geom_dotglyph(), geom_flowerglyph(), geom_metroglyph(), geom_pieglyph(), geom_profileglyph(), geom_starglyph(), geom_tileglyph()

Examples



library(ggplot2)

#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Prepare the data ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# Variables to map to glyphs
zs <- c("hp", "drat", "wt", "qsec", "vs", "am", "gear", "carb")

# Keep a copy of the original data
mtcars_fct <- mtcars

# Scaled numeric data
mtcars[zs] <- lapply(mtcars[zs], scales::rescale)

mtcars$cyl <- factor(mtcars$cyl)
mtcars$lab <- row.names(mtcars)

# Ordered factor data
mtcars_fct[zs[1:3]] <-
  lapply(mtcars_fct[zs[1:3]], function(x)
    ordered(cut(x, breaks = 3,
                labels = c("low", "medium", "high"))))

mtcars_fct[zs[4:8]] <-
  lapply(mtcars_fct[zs[4:8]], function(x)
    ordered(cut(x, breaks = 4,
                labels = c("tiny", "small", "medium", "large"))))

mtcars_fct$cyl <- factor(mtcars_fct$cyl)
mtcars_fct$lab <- row.names(mtcars_fct)

#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Mapped fill + scaled radius ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   alpha =  0.8) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Mapped fill + scaled area ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   scale.radius = FALSE, scale.area = TRUE,
                   alpha =  0.8) +
  ylim(c(-0, 550))


# \donttest{
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Mapped colour + scaled radius ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, colour = cyl),
                   cols = zs, size = 1.5, fill = "white",
                   alpha =  0.8, linewidth = 2) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Mapped colour + scaled area ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, colour = cyl),
                   cols = zs, size = 1.5, fill = "white",
                   scale.radius = FALSE, scale.area = TRUE,
                   alpha =  0.8, linewidth = 2) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Bubble layout variations ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# Annulus
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   alpha =  0.8) +
  ylim(c(-0, 550))


# Circle
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   layout = "circle",
                   alpha =  0.8) +
  ylim(c(-0, 550))


# Line
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   layout = "line",
                   alpha =  0.8) +
  ylim(c(-0, 550))


# Chain
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   layout = "chain",
                   alpha =  0.8) +
  ylim(c(-0, 550))


# Hub
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   layout = "hub",
                   alpha =  0.8) +
  ylim(c(-0, 550))


# Pack
ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   layout = "pack",
                   alpha =  0.8) +
  ylim(c(-0, 550))

#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Bubbles with multivariate colours ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp),
                   cols = zs, size = 1.5,
                   fill.bubble = RColorBrewer::brewer.pal(8, "Dark2"),
                   alpha =  0.8) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Gradient fill ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp),
                   cols = zs, size = 1.5,
                   fill.gradient = "viridis",
                   alpha =  0.8) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Faceted ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   alpha =  0.8) +
  ylim(c(-0, 550)) +
  facet_grid(. ~ cyl)


ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp, colour = cyl),
                   cols = zs, size = 1.5,
                   alpha =  0.8) +
  ylim(c(-0, 550)) +
  facet_grid(. ~ cyl)


ggplot(data = mtcars) +
  geom_bubbleglyph(aes(x = mpg, y = disp),
                   cols = zs, size = 1.5,
                   fill.bubble = RColorBrewer::brewer.pal(8, "Dark2"),
                   alpha =  0.8) +
  ylim(c(-0, 550)) +
  facet_grid(. ~ cyl)


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Repel glyphs ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp, colour = cyl)) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1.5,
                   alpha =  1, repel = TRUE) +
  ylim(c(-0, 550))


ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp, colour = cyl)) +
  geom_bubbleglyph(aes(x = mpg, y = disp, colour = cyl),
                   cols = zs, size = 1.5,
                   alpha =  1, repel = TRUE) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Grid lines (ordered factor variables) ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ggplot(data = mtcars_fct) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 0.5,
                   alpha =  0.8, draw.grid = TRUE) +
  ylim(c(-0, 550))


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Legend options ----
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

# Theme modifications for legend
legend_theme <-
  theme_bw(base_size = 7.5) +
  theme(legend.direction = "vertical",
        legend.box = "horizontal",
        legend.position = "bottom",
        legend.text = element_text(margin = margin(l = 7)),
        legend.key.height = unit(1, 'lines'))

# Glyph variable-wise legends
ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp, colour = cyl), show.legend = FALSE) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1,
                   alpha =  1, repel = TRUE) +
  ylim(c(-0, 550)) +
  scale_z_continuous(z = zs) +
  guide_z_order(z = zs, default_aes = "fill") +
  legend_theme


# Using custom guide
# bubbleglyphGrob
guide_bubblegrob <- bubbleglyphGrob(
  z = c(0.24, 0.3, 0.8, 1.4, 0.6, 0.33, 0.6, 0.25),
  layout = "annulus",
  size = 5)
# guide_bubblegrob <-
#   addlabel.glyphGrob(grob = guide_bubblegrob, label = zs,
#                      push = 1, segment = FALSE)

ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp, colour = cyl), show.legend = FALSE) +
  geom_bubbleglyph(aes(x = mpg, y = disp, fill = cyl),
                   cols = zs, size = 1,
                   alpha =  1, repel = TRUE) +
  ylim(c(-0, 550)) +
  guides(fill = guide_legend(order = 1, position = "right"),
         custom = guide_custom(guide_bubblegrob,
                               width = unit(0.1, "npc"),
                               height = unit(0.1, "npc"),
                               position = "bottom",
                               theme = theme(legend.margin = margin(t = 40, b = 30))))

# }