Package ‘gginnards’ (Explore the innards of ‘ggplot2’) is a set of extensions to R package ‘ggplot2’ and tools specially useful when learning how to write extensions and when debugging newly defined stats and geoms.
Occasionally it may be useful to edit gg
objects. A typical case are
packages that provide extensions to ‘ggplot2’ that construct and return
whole gg
objects instead of new statistics and geometries. In such
cases in can be useful to programatically edit these gg
objects.
Functions are provided for the manipulation of layers within
gg
objects.
As the variables returned in data
by many statistics depend on input,
some of these tools can be also useful in everyday plotting with
‘gplot2’ as a way of diagnosing problems.
Because of its nature, this package does not always play safe and nice even if it tries to. No exported or internal function or object should be imported or used in other packages, simply because they may change at any time. Although I intend to maintain the package, I will not attempt to actively keep it compatible with anything but the current version of ‘ggplot2’. Please, see the blog post Playing on the same team as your dependecy by Thomas Lin Pedersen.
This package was born when several functions were removed from package ‘ggpmisc’.
geom_debug()
by default prints the data
object received as input to
the console and generates no graphic output. As it takes as argument a
summary function, it allows great flexibility in how data
is
displayed. geom_debug()
is useful at any time when one needs to check
what variables are returned by statistics. Many statistics are well
documented and always return the same variables. For other statistics
even if well documented the returned variables in data
vary depending
on grouping and/or the arguments passed to them, in which case this
geometry can also be useful when debugging scripts.
Statistics that echo their data input to the R console aim at easing debugging during development of new geoms and statistics. They will also help those learning how ggplot grouping, panels and layers work.
A set of functions easy the manipulation of layers in ggplot objects, allowing deletion of any existing layer, insertion of new layers at any position, and reordering of the existing layers.
A function to drop unused variables from the data object embedded in
gg
and ggplot
objects serves as an additional example of a
manipulation that may be useful when dealing with very large datasets.
Companion functions are defined to explore the embedded data.
library(gginnards)
#> Loading required package: ggplot2
We print to the R console data
as seen as input by geometries and
statistics.
ggplot(mtcars, aes(cyl, mpg, color = mpg)) +
geom_point() +
geom_debug()
#> [1] "Summary (head) of input 'data' to 'draw_panel()':"
#> colour x y PANEL group
#> 1 #30648F 6 21.0 1 -1
#> 2 #30648F 6 21.0 1 -1
#> 3 #356E9D 4 22.8 1 -1
#> 4 #316692 6 21.4 1 -1
#> 5 #29577E 8 18.7 1 -1
#> 6 #275379 6 18.1 1 -1
We print to the R console colnames(data)
.
ggplot(mtcars, aes(cyl, mpg, color = mpg)) +
geom_point() +
geom_debug(summary.fun = colnames)
#> [1] "Summary of input 'data' to 'draw_panel()':"
#> [1] "colour" "x" "y" "PANEL" "group"
We print to the R console data
as returned by stat_summary()
and
seen as input by geometries.
ggplot(mtcars, aes(cyl, mpg, colour = factor(cyl))) +
stat_summary(fun.data = "mean_cl_boot") +
stat_summary(fun.data = "mean_cl_boot", geom = "debug")
#> [1] "Summary of input 'data' to 'draw_panel()':"
#> colour x group y ymin ymax PANEL flipped_aes
#> 1 #F8766D 4 1 26.66364 24.26341 29.21955 1 FALSE
#> 2 #00BA38 6 2 19.74286 18.68536 20.67143 1 FALSE
#> 3 #619CFF 8 3 15.10000 13.74268 16.24304 1 FALSE
We print to the R console data
as seen as input by statistics that
use a panel function.
ggplot(mtcars, aes(cyl, mpg, colour = factor(cyl))) +
stat_debug_panel()
#> [1] "Summary (head) of input 'data' to 'compute_panel()':"
#> x y colour PANEL group
#> 1 6 21.0 6 1 2
#> 2 6 21.0 6 1 2
#> 3 4 22.8 4 1 1
#> 4 6 21.4 6 1 2
#> 5 8 18.7 8 1 3
#> 6 6 18.1 6 1 2
We build object p
of class gg
(a ggplot). We query the number of
layers and the position of layers by the class of the ggproto
object.
p <-
ggplot(mtcars, aes(cyl, mpg)) +
geom_point(size = 3) +
stat_summary(fun.data = "mean_cl_boot", color = "red", size = 2)
num_layers(p)
#> [1] 2
which_layers(p, "GeomPoint")
#> [1] 1
which_layers(p, "StatSummary")
#> [1] 2
p
move_layers(p, "GeomPoint", position = "top")
Installation of the most recent stable version from CRAN:
install.packages("gginnards")
Installation of the current unstable version from GitHub:
# install.packages("devtools")
devtools::install_github("aphalo/gginnards")
HTML documentation is available at (https://docs.r4photobiology.info/gginnards/), including two vignettes.
News about updates are regularly posted at (https://www.r4photobiology.info/).
Please report bugs and request new features at (https://github.com/aphalo/gginnards/issues). Pull requests are welcome at (https://github.com/aphalo/gginnards).
If you use this package to produce scientific or commercial publications, please cite according to:
citation("gginnards")
#> To cite package 'gginnards' in publications use:
#>
#> Aphalo P (2023). _gginnards: Explore the Innards of 'ggplot2'
#> Objects_. https://www.r4photobiology.info,
#> https://github.com/aphalo/gginnards.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {gginnards: Explore the Innards of 'ggplot2' Objects},
#> author = {Pedro J. Aphalo},
#> year = {2023},
#> note = {https://www.r4photobiology.info, https://github.com/aphalo/gginnards},
#> }
© 2016-2023 Pedro J. Aphalo (pedro.aphalo@helsinki.fi). Released under the GPL, version 2 or greater. This software carries no warranty of any kind.
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