Add Tile Glyphs as a Scatterplot

The tileglyph geom is used to plot multivariate data as tile glyphs similar to 'autoglyph' (Beddow 1990) or 'stripe glyph' (Fuchs et al. 2013) in a scatterplot.

Usage

geom_tileglyph(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  cols = character(0L),
  colour = "black",
  ratio = 1,
  nrow = 1,
  linewidth = 1,
  fill.gradient = NULL,
  show.legend = NA,
  repel = FALSE,
  repel.control = gglyph.repel.control(),
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by aes() or 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, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

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

Name of columns specifying the variables to be plotted in the glyphs as a character vector.

colour

The colour of the tile glyphs.

ratio

The aspect ratio (height / width).

nrow

The number of rows.

linewidth

The line width of the tile glyphs.

fill.gradient

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

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.

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 gglyph.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. borders().

Value

A geom layer.

Aesthetics

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

x
y
alpha
group
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.

References

Beddow J (1990). “Shape coding of multidimensional data on a microcomputer display.” In Proceedings of the First IEEE Conference on Visualization: Visualization `90, 238--246. ISBN 978-0-8186-2083-6.

Fuchs J, Fischer F, Mansmann F, Bertini E, Isenberg P (2013). “Evaluation of alternative glyph designs for time series data in a small multiple setting.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 3237--3246. ISBN 978-1-4503-1899-0.

Examples


# Scale the data
zs <- c("hp", "drat", "wt", "qsec", "vs", "am", "gear", "carb")
mtcars[ , zs] <- lapply(mtcars[ , zs], scales::rescale)

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

library(ggplot2)
theme_set(theme_bw())
options(ggplot2.discrete.colour = RColorBrewer::brewer.pal(8, "Dark2"))
options(ggplot2.discrete.fill = RColorBrewer::brewer.pal(8, "Dark2"))

ggplot(data = mtcars) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 2,
                 fill.gradient = "Blues",
                 alpha =  0.5) +
  ylim(c(-0, 550))


ggplot(data = mtcars) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 2,
                 nrow = 2,
                 fill.gradient = "Greens",
                 alpha =  0.5) +
  ylim(c(-0, 550))


ggplot(data = mtcars) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 1,
                 ratio = 4,
                 fill.gradient = "RdYlBu",
                 alpha =  0.5) +
  ylim(c(-0, 550))


ggplot(data = mtcars) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 1,
                 ratio = 4, nrow = 2,
                 fill.gradient = "viridis",
                 alpha =  0.5) +
  ylim(c(-0, 550))


# Repel glyphs
ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp)) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 2,
                 fill.gradient = "Blues",
                 alpha = 1, repel = TRUE) +
  ylim(c(-0, 550))


ggplot(data = mtcars) +
  geom_point(aes(x = mpg, y = disp)) +
  geom_tileglyph(aes(x = mpg, y = disp),
                 cols = zs, size = 1,
                 ratio = 4, nrow = 2,
                 fill.gradient = "viridis",
                 alpha = 1, repel = TRUE) +
  ylim(c(-0, 550))