Secondary color scale that ramps from another color (ggplot2 scale)

Source: R/scale_colour_ramp.R

This scale creates a secondary scale that modifies the fill or color scale of geoms that support it (geom_lineribbon() and geom_slabinterval()) to "ramp" from a secondary color (by default white) to the primary fill color (determined by the standard color or fill aesthetics). It uses the partial_colour_ramp() data type.

scale_colour_ramp_continuous(
  from = "white",
  ...,
  limits = function(l) c(min(0, l[[1]]), l[[2]]),
  range = c(0, 1),
  guide = "legend",
  aesthetics = "colour_ramp"
)

scale_color_ramp_continuous(
  from = "white",
  ...,
  limits = function(l) c(min(0, l[[1]]), l[[2]]),
  range = c(0, 1),
  guide = "legend",
  aesthetics = "colour_ramp"
)

scale_colour_ramp_discrete(
  from = "white",
  ...,
  range = c(0.2, 1),
  aesthetics = "colour_ramp"
)

scale_color_ramp_discrete(
  from = "white",
  ...,
  range = c(0.2, 1),
  aesthetics = "colour_ramp"
)

scale_fill_ramp_continuous(..., aesthetics = "fill_ramp")

scale_fill_ramp_discrete(..., aesthetics = "fill_ramp")

Arguments

from

<string> The color to ramp from. Corresponds to 0 on the scale.

...

Arguments passed to underlying scale or guide functions. E.g. scale_colour_ramp_discrete() passes arguments to discrete_scale(), scale_colour_ramp_continuous() passes arguments to continuous_scale(). See those functions for more details.

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()).

range

<length-2 numeric> Minimum and maximum values after the scale transformation. These values should be between 0 (the from color) and 1 (the color determined by the fill aesthetic).

guide

<Guide | string> A function used to create a guide or its name. For scale_colour_ramp_continuous() and scale_fill_ramp_continuous(), guide_rampbar() can be used to create gradient color bars. See guides() for information on other guides.

aesthetics

<character> Names of aesthetics to set scales for.

Value

A ggplot2::Scale representing a scale for the colour_ramp and/or fill_ramp aesthetics for ggdist geoms. Can be added to a ggplot() object.

Details

These scales transform data into partial_colour_ramps. Each partial_colour_ramp is a pair of two values: a from colour and a numeric amount between 0 and 1 representing a distance between from and the target color (where 0 indicates the from color and 1 the target color).

The target color is determined by the corresponding aesthetic: for example, the colour_ramp aesthetic creates ramps between from and whatever the value of the colour aesthetic is; the fill_ramp aesthetic creates ramps between from and whatever the value of the fill aesthetic is. When the colour_ramp aesthetic is set, ggdist geometries will modify their colour by applying the colour ramp between from and colour (and similarly for fill_ramp and fill).

Colour ramps can be applied (i.e. translated into colours) using ramp_colours(), which can be used with partial_colour_ramp() to implement geoms that make use of colour_ramp or fill_ramp scales.

See also

Other ggdist scales: scale_side_mirrored(), scale_thickness, sub-geometry-scales

Other colour ramp functions: guide_rampbar(), partial_colour_ramp(), ramp_colours()

Author

Matthew Kay

Examples


library(dplyr)
library(ggplot2)
library(distributional)

tibble(d = dist_uniform(0, 1)) %>%
  ggplot(aes(y = 0, xdist = d)) +
  stat_slab(aes(fill_ramp = after_stat(x)))


tibble(d = dist_uniform(0, 1)) %>%
  ggplot(aes(y = 0, xdist = d)) +
  stat_slab(aes(fill_ramp = after_stat(x)), fill = "blue") +
  scale_fill_ramp_continuous(from = "red")


# you can invert the order of `range` to change the order of the blend
tibble(d = dist_normal(0, 1)) %>%
  ggplot(aes(y = 0, xdist = d)) +
  stat_slab(aes(fill_ramp = after_stat(cut_cdf_qi(cdf))), fill = "blue") +
  scale_fill_ramp_discrete(from = "red", range = c(1, 0))