scale_colour_steps {ggshadow}

Binned gradient colour scales

Description

'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][scale_colour_gradient] family and works in the same way.

Usage

scale_shadowcolour_steps(
  ...,
  low = "#132B43",
  high = "#56B1F7",
  space = "Lab",
  na.value = "grey50",
  guide = "coloursteps",
  aesthetics = "shadowcolour"
)

scale_shadowcolour_steps2(
  ...,
  low = muted("red"),
  mid = "white",
  high = muted("blue"),
  midpoint = 0,
  space = "Lab",
  na.value = "grey50",
  guide = "coloursteps",
  aesthetics = "shadowcolour"
)

scale_shadowcolour_stepsn(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = "coloursteps",
  aesthetics = "shadowcolour",
  colors
)

Arguments

...

Arguments passed on to ggplot2::binned_scale

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:

• NULL for no labels

• waiver() for the default labels computed by the transformation object

• A character vector giving labels (must be same length as breaks)

• A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

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.

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?

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().

show.limits

should the limits of the scale appear as ticks

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

low, high

Colours for low and high ends of the gradient.

space

colour space in which to calculate gradient. Must be "Lab" - other values are deprecated.

na.value

Colour to use for missing values

guide

Type of legend. Use "colourbar" for continuous colour bar, or "legend" for discrete colour legend.

aesthetics

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").

mid

colour for mid point

midpoint

The midpoint (in data value) of the diverging scale. Defaults to 0.

colours, colors

Vector of colours to use for n-colour gradient.

values

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.

Details

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.

Value

a scale object to add to a plot.

See Also

[scales::seq_gradient_pal()] for details on underlying palette

Other colour scales: scale_brewer, scale_colour_hue, scale_gradient, scale_grey, scale_viridis

Examples

library( ggplot2 )
p <- ggplot(mtcars, aes(wt, mpg, shadowcolor=gear))
p + geom_shadowpoint() + scale_shadowcolour_steps() + guides(shadowcolour='none')

library( ggplot2 )
p <- ggplot(mtcars, aes(wt, mpg, shadowcolor=gear))
p + geom_shadowpoint() + scale_shadowcolour_steps2() + guides(shadowcolour='none')

library( ggplot2 )
p <- ggplot(mtcars, aes(wt, mpg, shadowcolor=gear))
p <- p + geom_shadowpoint() + scale_shadowcolour_stepsn(colours=c('red', 'yellow'))
p + guides(shadowcolour='none')