scale_*_steps
creates a two colour binned gradient (low-high),
scale_*_steps2
creates a diverging binned colour gradient (low-mid-high),
and scale_*_stepsn
creates a n-colour binned gradient. These scales are
binned variants of the gradient scale family and
works in the same way.
scale_colour_steps(
...,
low = "#132B43",
high = "#56B1F7",
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "colour"
)
scale_colour_steps2(
...,
low = muted("red"),
mid = "white",
high = muted("blue"),
midpoint = 0,
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "colour"
)
scale_colour_stepsn(
...,
colours,
values = NULL,
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "colour",
colors
)
scale_fill_steps(
...,
low = "#132B43",
high = "#56B1F7",
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "fill"
)
scale_fill_steps2(
...,
low = muted("red"),
mid = "white",
high = muted("blue"),
midpoint = 0,
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "fill"
)
scale_fill_stepsn(
...,
colours,
values = NULL,
space = "Lab",
na.value = "grey50",
guide = "coloursteps",
aesthetics = "fill",
colors
)
Arguments passed on to binned_scale
n.breaks
The number of break points to create if breaks are not given directly.
nice.breaks
Logical. Should breaks be attempted placed at nice values
instead of exactly evenly spaced between the limits. If TRUE
(default)
the scale will ask the transformation object to create breaks, and this
may result in a different number of breaks than requested. Ignored if
breaks are given explicitly.
right
Should values on the border between bins be part of the right (upper) bin?
show.limits
should the limits of the scale appear as ticks
name
The name of the scale. Used as the axis or legend title. If
waiver()
, the default, the name of the scale is taken from the first
mapping used for that aesthetic. If NULL
, the legend title will be
omitted.
breaks
One of:
NULL
for no breaks
waiver()
for the default breaks computed by the
transformation object
A numeric vector of positions
A function that takes the limits as input and returns breaks
as output (e.g., a function returned by scales::extended_breaks()
).
Also accepts rlang lambda function notation.
labels
One of:
limits
One of:
NULL
to use the default scale range
A numeric vector of length two providing limits of the scale.
Use NA
to refer to the existing minimum or maximum
A function that accepts the existing (automatic) limits and returns
new limits. Also accepts rlang lambda function
notation.
Note that setting limits on positional scales will remove data outside of the limits.
If the purpose is to zoom, use the limit argument in the coordinate system
(see coord_cartesian()
).
oob
One of:
Function that handles limits outside of the scale limits (out of bounds). Also accepts rlang lambda function notation.
The default (scales::censor()
) replaces out of
bounds values with NA
.
scales::squish()
for squishing out of bounds values into range.
scales::squish_infinite()
for squishing infinite values into range.
expand
For position scales, a vector of range expansion constants used to add some
padding around the data to ensure that they are placed some distance
away from the axes. Use the convenience function expansion()
to generate the values for the expand
argument. The defaults are to
expand the scale by 5% on each side for continuous variables, and by
0.6 units on each side for discrete variables.
trans
For continuous scales, the name of a transformation object or the object itself. Built-in transformations include "asn", "atanh", "boxcox", "date", "exp", "hms", "identity", "log", "log10", "log1p", "log2", "logit", "modulus", "probability", "probit", "pseudo_log", "reciprocal", "reverse", "sqrt" and "time".
A transformation object bundles together a transform, its inverse,
and methods for generating breaks and labels. Transformation objects
are defined in the scales package, and are called <name>_trans
(e.g.,
scales::boxcox_trans()
). You can create your own
transformation with scales::trans_new()
.
position
For position scales, The position of the axis.
left
or right
for y axes, top
or bottom
for x axes.
super
The super class to use for the constructed scale
Colours for low and high ends of the gradient.
Colours for low and high ends of the gradient.
colour space in which to calculate gradient. Must be "Lab" - other values are deprecated.
Colour to use for missing values
Type of legend. Use "colourbar"
for continuous
colour bar, or "legend"
for discrete colour legend.
Character string or vector of character strings listing the
name(s) of the aesthetic(s) that this scale works with. This can be useful, for
example, to apply colour settings to the colour
and fill
aesthetics at the
same time, via aesthetics = c("colour", "fill")
.
colour for mid point
The midpoint (in data value) of the diverging scale. Defaults to 0.
Vector of colours to use for n-colour gradient.
if colours should not be evenly positioned along the gradient
this vector gives the position (between 0 and 1) for each colour in the
colours
vector. See rescale()
for a convenience function
to map an arbitrary range to between 0 and 1.
Vector of colours to use for n-colour gradient.
Default colours are generated with munsell and
mnsl(c("2.5PB 2/4", "2.5PB 7/10"))
. Generally, for continuous
colour scales you want to keep hue constant, but vary chroma and
luminance. The munsell package makes this easy to do using the
Munsell colour system.
scales::seq_gradient_pal()
for details on underlying
palette, scale_colour_gradient()
for continuous scales without binning.
Other colour scales:
scale_alpha()
,
scale_colour_brewer()
,
scale_colour_continuous()
,
scale_colour_gradient()
,
scale_colour_grey()
,
scale_colour_hue()
,
scale_colour_viridis_d()
df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100)
)
# Use scale_colour_steps for a standard binned gradient
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_steps()
# Get a divergent binned scale with the *2 variant
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_steps2()
# Define your own colour ramp to extract binned colours from
ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +
scale_colour_stepsn(colours = terrain.colors(10))