Fabio Crameri's bukavu Multi-Sequential Color Scheme

## Usage

``````scale_colour_bukavu(
...,
reverse = FALSE,
range = c(0, 1),
midpoint = 0,
aesthetics = "colour"
)

scale_color_bukavu(
...,
reverse = FALSE,
range = c(0, 1),
midpoint = 0,
aesthetics = "colour"
)

scale_fill_bukavu(
...,
reverse = FALSE,
range = c(0, 1),
midpoint = 0,
aesthetics = "fill"
)``````

## Source

Crameri, F. (2021). Scientific colour maps. Zenodo, v7.0. doi:10.5281/zenodo.4491293

## Arguments

...

Arguments passed to `ggplot2::continuous_scale()`.

reverse

A `logical` scalar. Should the resulting vector of colors be reversed?

range

A length-two `numeric` vector specifying the fraction of the scheme's color domain to keep.

midpoint

A length-one `numeric` vector giving the midpoint (in data value) of the diverging scale. Defaults to `0`.

aesthetics

A `character` string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with.

## Value

A continuous scale.

## Sequential Color Schemes

If more colors than defined are needed from a given scheme, the color coordinates are linearly interpolated to provide a continuous version of the scheme.

 Palette Max. `batlow` 256 `batlowW` 256 `batlowK` 256 `devon` 256 `lajolla` 256 `bamako` 256 `davos` 256 `bilbao` 256 `nuuk` 256 `oslo` 256 `grayC` 256 `hawaii` 256 `lapaz` 256 `tokyo` 256 `buda` 256 `acton` 256 `turku` 256 `imola` 256 `oleron`* 256 `bukavu`* 256 `fes`* 256

*: multisequential color schemes.

## References

Crameri, F. (2018). Geodynamic diagnostics, scientific visualisation and StagLab 3.0. Geosci. Model Dev., 11, 2541-2562. doi:10.5194/gmd-11-2541-2018

Crameri, F., Shephard, G. E. & Heron, P. J. (2020). The misuse of colour in science communication. Nature Communications, 11, 5444. doi:10.1038/s41467-020-19160-7

Other multi sequential color schemes: `scale_crameri_fes`, `scale_crameri_oleron`

Other Fabio Crameri's color schemes: `scale_crameri_acton`, `scale_crameri_bam`, `scale_crameri_bamO`, `scale_crameri_bamako`, `scale_crameri_batlow`, `scale_crameri_batlowK`, `scale_crameri_batlowW`, `scale_crameri_berlin`, `scale_crameri_bilbao`, `scale_crameri_broc`, `scale_crameri_brocO`, `scale_crameri_buda`, `scale_crameri_cork`, `scale_crameri_corkO`, `scale_crameri_davos`, `scale_crameri_devon`, `scale_crameri_fes`, `scale_crameri_grayC`, `scale_crameri_hawaii`, `scale_crameri_imola`, `scale_crameri_lajolla`, `scale_crameri_lapaz`, `scale_crameri_lisbon`, `scale_crameri_nuuk`, `scale_crameri_oleron`, `scale_crameri_oslo`, `scale_crameri_roma`, `scale_crameri_romaO`, `scale_crameri_tofino`, `scale_crameri_tokyo`, `scale_crameri_turku`, `scale_crameri_vanimo`, `scale_crameri_vik`, `scale_crameri_vikO`

N. Frerebeau

## Examples

``````data(volcano)

volcan <- data.frame(
x = rep(1:ncol(volcano), each = nrow(volcano)),
y = rep(1:nrow(volcano), times = ncol(volcano)),
z = as.numeric(volcano)
)

ggplot2::ggplot(volcan, ggplot2::aes(x, y, fill = z)) +
ggplot2::geom_raster() +
scale_fill_oleron(midpoint = 125)

``````