A quick demonstration of capping the lines.
First, load the package, generate a dataset and display it.
library(ggplot2)
library(lemon)
dat1 <- data.frame(
gp = factor(rep(letters[1:3], each = 10)),
y = rnorm(30),
cl = sample.int(3, 30, replace=TRUE),
cl2 = sample(c('a','b','c'), 30, replace=TRUE)
)
my.theme <- theme_light()
(
p <- ggplot(dat1, aes(gp, y)) + geom_point() + my.theme
)
NB: In order to manipulate the axis lines, they must be drawn. Modify the theme so the panel.border
is not drawn (it will be on top of the axis lines), and have the axis lines drawn:
my.theme <- my.theme + theme(panel.border=element_blank(),
axis.line = element_line(),
axis.ticks = element_line(colour='black'))
p <- p + my.theme
Now, let’s have some fun.
We cap the bottom axis line to the right-most tick. The left end is also capped by the amount specified with the gap
argument (at time of writing, defaulted at 0.01
).
To keep the axis lines consistent, we also specify the left
argument, which still caps the left axis line by the amount specified with the gap
argument.
To avoid overplotting, we can apply a jitter. To emphasise that the x-axis is categorical, we can place brackets. We finally polish the plot by removing the redundant vertical grid lines.
ggplot(dat1, aes(gp, y)) + geom_point(position=position_jitter(width=0.2, height=0)) +
coord_capped_cart(left='none', bottom=brackets_horizontal()) +
my.theme + theme(panel.grid.major.x = element_blank())
coord
objectsggplot2’s Cartesian coordinates systems, coord_cartesian
, have been extended to allow for flexible specification of how axes are drawn. You’ve seen them above. The following table summarises the connection between ggplot2’s coord functions and those of lemon.
ggplot2 | lemon’s flexible | lemon’s short hand |
---|---|---|
coord_cartesian |
coord_flex_cart |
coord_capped_cart |
coord_flip |
coord_flex_flip |
coord_capped_flip |
coord_fixed |
coord_flex_fixed |
– |
The short hand functions in the table’s right column simply are almost identical to those in the middle column. If one of the side arguments are specified with a character value, the relevant axis drawing function is used. You can however choose to use e.g. brackets_horizontal
in place.
The functions capped_horizontal
or brackets_vertical
returns a function that is called when ggplot2 prints the plot. In this package, we use ggplot2 to build the axes, then modify in place the return grobs.
The function is called by the coord
objects when printing the plot, and is called with the arguments
panel_params$guides position, theme
The function should then return a grob. Some pointers to how it is used can be found in ggplot2’s help pages on ggproto (?"ggplot2-ggproto"
)
The arguments are as follows1
panel_params$guide
contains 4 lists, named respectively x
, x.sec
, y
and y.sec
, corresponding to the x- and y-axis, and .sec
refers to the secondary axis.
Drawing these lines is done with the function ggplot2:::panel_guides_grob
which is found in the file R/coord-cartesian.r
.
For the arguments position
and theme
, values passed are "top"
, "bottom"
, "left"
or "right"
for position
, while theme
is a theme-object, as described in the bottom.
guides
is a list of elements for drawing an axis line and its ticks. Following is for a secondary axis to the right:
$title
list()
attr(,"class")
[1] "waiver"
$check.overlap
[1] FALSE
$angle
NULL
$n.dodge
[1] 1
$order
[1] 0
$position
[1] "right"
$available_aes
[1] "x" "y"
$name
[1] "axis_y"
$key
y .value .label x
1 0.2442442 -1.249523622 -2.5 1
2 0.5105105 -0.001656758 0.0 1
3 0.7777778 1.250901335 2.5 1
$hash
[1] "803d9baa63668f8906bd6c98dd767655"
attr(,"class")
[1] "guide" "axis"
The data.frame $key
is interesting, as it describes the position in both y- and x-direction. Here is a corresponding data.frame for a x-axis in the bottom:
$key
x .value .label y
1 0.1875 a a 0
2 0.5000 b b 0
3 0.8125 c c 0
Notice that the x- and y-values are relative to the viewport, i.e. in “npc” units.
theme
: The plot’s theme. This is however not in absolute terms, e.g. so text sizes may be described in relative terms to the base size. To resolve a usable gp
(graphic parameters, see ?grid::gpar
) for a grob, use ggplot2:::element_render(theme, 'axis.text.x')
, in which the second argument would resolve to the labels of the x-axis.
The brackets comes in two orientations: brackets_horizontal
and brackets_vertical
. If you attempt to use a vertical bracket on a horizontal axis, it will fail with a undescriptive error.
The bracket functions accept a direction
argument, which can be used to control which direction the end-points are pointing:
p <- ggplot(mpg, aes(cyl, hwy, colour=class)) +
geom_point(position=position_jitter(width=0.3)) +
scale_x_continuous(breaks=c(4,5,6,8), sec.axis=dup_axis()) +
scale_y_continuous(sec.axis=dup_axis()) +
coord_flex_cart(bottom=brackets_horizontal(),
top=brackets_horizontal(direction='down'),
left=brackets_vertical(),
right=brackets_vertical(direction='right')) +
my.theme
p
The look of the brackets are controlled via theme(axis.ticks)
. The length of the end-point are controlled via the theme theme(axis.ticks.length)
. If these needs to be specified for each margin, use the argument tick.length
:
p <- ggplot(mpg, aes(cyl, hwy, colour=class)) +
geom_point(position=position_jitter(width=0.3)) +
coord_flex_cart(bottom=brackets_horizontal(tick.length=0),
left=brackets_vertical(tick.length = unit(1, 'cm'))) +
my.theme
p
As shown above, using tick.length=unit(0, 'cm')
results in a flat line.
Having produced such wonderous axes, it is a pity they are not plotted around all panels when using faceting.
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
(d <- ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = clarity)) +
coord_capped_cart(bottom='none', left='bottom') +
facet_grid(.~cut) + my.theme
)
facet_grid
and facet_wrap
have been implemented in versions that display the axis lines (and labels) on all panels. They work exactly like ggplot2’s functions, and are named with _rep_
:
If we want the labels shown as well, use the argument:
It also works for facet_wrap
:
Finally, the legend can be repositioned to fit in a panel by using reposition_legend
. See the vignette legend
. The addition of theme(legend.background)
is merely to provide a border around the legend.
As of lemon v0.4.2, you can now use symmetric y- og x-axis scales.
The same effect could be achieved with coord_cartesian
or use of scale_y_continuous
; however when used with a facet where each row (or column) should scale to the data, scale_x_symmetric
and scale_y_symmetric
ensures the data will remain centered.
To get the contents of the arguments, I usually include a line in the function’s code to save them as a RDS object: saveRDS(list(guides=panel_params$guides, position=position, theme=theme), file='whatever.rds')
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