Package ‘ggpmisc’ focuses mainly on plot annotations. The new features added in this version required quite minor code changes but add features that I hope will be found useful.
Changes from version 0.3.5 the most recent CRAN release, are:
Annotations using NPC coordinates
NPC or native plot coordinates, are very useful for annotations. On the other hand, they are not of any use for plotting actual data. The geometries using this kind of position coordinates defined in ‘ggpmisc’ make it possible to have different annotations in the different panels when using facets. Traditional annotations in ‘ggplot2’ do not use the data, but instead take as arguments constant values for the aesthetics, and consequently add identical annotations to all panels. Annotations in ‘ggplot2’ use data coordinates. In many cases, the desired position of annotations is unrelated to the data, but instead related to the native coordinates of the plotting viewport. Using NPC coordinates for annotations allows consistent positioning, which is very important from the graphical design perspective.
Starting from version 0.3.6 ‘ggpmisc’ exports a modified definition of
annotate() from ‘ggplot2’. The modification adds support of the position aesthetics
npcy retaining all other functionality unaltered. As a consequence geometries
"grob_npc" can now be used as the first argument to
annotate(). In addition single ggplots, data frames and grobs as well as lists of such objects are accepted arguments to
# plot to be inset
p <- ggplot(mtcars, aes(factor(cyl), mpg, colour = factor(cyl))) +
labs(y = NULL) +
theme_bw(9) + theme(legend.position = "none")
# main plot with p as an inset
ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) +
annotate("plot_npc", npcx = "left", npcy = "bottom", label = p) +
expand_limits(y = 0, x = 0)
Tagging equations with group labels (experimental)
Starting from version 0.3.6
stat_poly_eq() supports use of grouping with equations and identifying them by using labels. Previously use of the color aesthetic was the only way of “linking” equations to plotted curves, which is frequently distracting or unavailable for printing. After some past failed attempts at implementing this, I recently realized that using a pseudo-aesthetic made implementation very easy and its use flexible and straightforward. The catch is that this relies on undocumented behavior of ‘ggplot2’ and will not necessarily work with future versions of ‘ggplot2’. Statistic
stat_poly_eq() now copies
grp.label from its input into its returned value. One can map any variable to the pseudo-aesthetic
grp.label to achieve this. Values are passed to the output only if all values within the group are the same, otherwise
grp.label is filled with
NA. The signature of
stat_poly_eq() remains unchanged.
my.formula <- y ~ x
ggplot(mtcars, aes(wt, mpg,
linetype = factor(cyl), shape = factor(cyl),
grp.label = factor(cyl))) +
stat_smooth(formula = my.formula, method = "lm", colour = "black") +
stat_poly_eq(aes(label = stat(paste("bold(\"cyl\"~~", grp.label,
"*':')~~~", eq.label, sep = ""))),
formula = my.formula, label.x = "right", parse = TRUE) +
Marking and or labeling group centroids
stat_centroid() applies the same function to
y and this function defaults to
mean(). In the case of
stat_summary_xy() the functions applied to
y are passed as separate arguments, and they both default to simply copying their input.
Starting from version 0.3.6, statistic
stat_poly_eq() can optionally generate character strings encoded in markdown suitable for
geom_richtext() from package ‘ggtext’.
Acknowlegement: This update was encouraged by recent questions at stackoverflow. The tag
[ggpmisc] is in use at stackoverflow for questions related to this package.
Documentation web site at http://docs.r4photobiology.info/ggpmisc/ includes all help pages, with output from all examples, and vignettes in HTML format.
NOTE: The new version of the package is on its way to CRAN.
Please raise issues concerning bugs or enhancements to this package through Bitbucket https://bitbucket.org/aphalo/ggpmisc/issues.