knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 4, fig.height = 4 )
tactile introduces a few new high-level functions to the latticeverse. This vignette will be updated as new functions are added.
ternaryplot()
: Ternary plotsTernary plots display proportions of three variables on a two-dimensional grid
are popular in compositional analysis. tactile can be used to generate
ternary plots with ternaryplot()
which takes formula, matrix, or
data.frame objects an input. The formula method -- the focus of this
vignette -- used the form top ~ left * right
in terms of the
dimensions of the ternary diagram.
To showcase the use of ternaryplot()
we'll use data from an article
by Grove and Jenkins that has been imported into tactile and made available
simply by calling feldspar
. We begin with the simplest form of a
ternary plot.
library(tactile) ternaryplot(Or ~ An * Ab, data = feldspar)
All of the bells and whistles of lattice graphics are available in tactile too,
and we may benefit here by, for instance, grouping variables by the
coexisting feldspar factor Feldspar
. Here, we also remove the useless
box around the plot.
ternaryplot(Or ~ An * Ab, groups = Feldspar, data = feldspar, auto.key = list(space = "right"), par.settings = list(axis.line = list(col = "transparent")) )
Another feature to visualize the compositions, which would make more sense
with a larger dataset, is to add two-dimensional density estimates. We do this
by setting the density
argument to TRUE
. Instead of superposing the
two types of composite feldspars, we now condition instead.
ternaryplot(Or ~ An * Ab | Feldspar, data = feldspar, density = TRUE)
These density estimations are produced by first applying a isometric
log transformation and then computing density estimates with MASS::kde2d()
before returning the coordinates to the ternary coordinate space.
One more feature that is available is to model a response on our compositional data. We (obviously) need a separate outcome variable for this and will here use the temperature of the reaction from the feldspar experiments, offering examples of a version with region fills and one with contours.
ternaryplot(Or ~ An * Ab, response = Pressure, data = feldspar, contour = FALSE ) ternaryplot(Or ~ An * Ab, response = Pressure, data = feldspar, region = FALSE)
bubbleplot()
: BubbleplotsBubble plots are simple scatter plots that have been extended to a third dimensions by mapping a third variable to the size (area) of the plot symbols, which theoretically could be anything but usually is points. Bubble plots were made famous by the late Hans Rosling.
Bubble plots in tactile are available with bubbleplot()
and
take a formula of the type bubblesize ~ x * y
as its first argument. We
illustrate with with the mtcars
data set from R that sports the
features of 32 cars from the 1974 Motor Trend US magazine. We start
by mapping the displacement to the bubble size against horsepower (hp)
and weight (wt).
bubbleplot(disp ~ hp * wt, groups = cyl, data = mtcars, auto.key = TRUE)
More elaborate designs can be fashioned if we were to combine the plot with some of the specialized panel functions from lattice. Here, we also change to a filled circle design with semitransparent bubbles.
bubbleplot(disp ~ hp * wt | factor(cyl), data = mtcars, auto.key = TRUE, pch = 16, alpha = 0.5, layout = c(3, 1), panel = function(x, y, z, ...) { panel.lmline(x, y, ...) panel.bubbleplot(x, y, z, ...) } )
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