library(khroma)
1. Introduction
Crameri (2018) offers carefully chosen schemes, ready for mapping data, with colors that are:
- Perceptually uniform,
- Perceptually ordered,
- Color vision deficiency friendly,
- Readable as black and white print,
- Citable & reproducible.
All the scales presented in Crameri (2021) are implemented here, for use with base R graphics, ggplot2 or ggraph.
2. Diverging data
2.1 broc
broc <- color("broc")
plot(broc(256))
plot of chunk crameri_div_broc
2.2 cork
cork <- color("cork")
plot(cork(256))
plot of chunk crameri_div_cork
2.3 vik
vik <- color("vik")
plot(vik(256))
plot of chunk crameri_div_vik
2.4 lisbon
lisbon <- color("lisbon")
plot(lisbon(256))
plot of chunk crameri_div_lisbon
2.5 tofino
tofino <- color("tofino")
plot(tofino(256))
plot of chunk crameri_div_tofino
2.6 berlin
berlin <- color("berlin")
plot(berlin(256))
plot of chunk crameri_div_berlin
2.7 roma
roma <- color("roma")
plot(roma(256))
plot of chunk crameri_div_roma
2.8 bam
bam <- color("bam")
plot(bam(256))
plot of chunk crameri_div_bam
2.9 vanimo
vanimo <- color("vanimo")
plot(vanimo(256))
plot of chunk crameri_div_vanimo
3. Sequential data
3.1 batlow
batlow <- color("batlow")
plot(batlow(256))
plot of chunk crameri_seq_batlow
3.2 batlowW
batlowW <- color("batlowW")
plot(batlowW(256))
plot of chunk crameri_seq_batlowW
3.3 batlowK
batlowK <- color("batlowK")
plot(batlowK(256))
plot of chunk crameri_seq_batlowK
3.4 devon
devon <- color("devon")
plot(devon(256))
plot of chunk crameri_seq_devon
3.5 lajolla
lajolla <- color("lajolla")
plot(lajolla(256))
plot of chunk crameri_seq_lajolla
3.6 bamako
bamako <- color("bamako")
plot(bamako(256))
plot of chunk crameri_seq_bamako
3.7 davos
davos <- color("davos")
plot(davos(256))
plot of chunk crameri_seq_davos
3.8 bilbao
bilbao <- color("bilbao")
plot(bilbao(256))
plot of chunk crameri_seq_bilbao
3.9 nuuk
nuuk <- color("nuuk")
plot(nuuk(256))
plot of chunk crameri_seq_nuuk
3.10 oslo
oslo <- color("oslo")
plot(oslo(256))
plot of chunk crameri_seq_oslo
3.11 grayC
grayC <- color("grayC")
plot(grayC(256))
plot of chunk crameri_seq_grayC
3.12 hawaii
hawaii <- color("hawaii")
plot(hawaii(256))
plot of chunk crameri_seq_hawaii
3.13 lapaz
lapaz <- color("lapaz")
plot(lapaz(256))
plot of chunk crameri_seq_lapaz
3.14 tokyo
tokyo <- color("tokyo")
plot(tokyo(256))
plot of chunk crameri_seq_tokyo
3.15 buda
buda <- color("buda")
plot(buda(256))
plot of chunk crameri_seq_buda
3.16 acton
acton <- color("acton")
plot(acton(256))
plot of chunk crameri_seq_acton
3.17 turku
turku <- color("turku")
plot(turku(256))
plot of chunk crameri_seq_turku
3.18 imola
imola <- color("imola")
plot(imola(256))
plot of chunk crameri_seq_imola
4. Multi-sequential data
4.1 oleron
oleron <- color("oleron")
plot(oleron(256))
plot of chunk crameri_seq_oleron
4.2 bukavu
bukavu <- color("bukavu")
plot(bukavu(256))
plot of chunk crameri_seq_bukavu
4.3 fes
fes <- color("fes")
plot(fes(256))
plot of chunk crameri_seq_fes
5. References
Crameri, F. 2018. “Geodynamic Diagnostics, Scientific Visualisation and StagLab 3.0.” Geoscientific Model Development 11 (6): 2541-2562. DOI: 10.5194/gmd-11-2541-2018.
Crameri, F. 2021. Scientific Colour Maps (version 7.0.0). Zenodo. DOI: 10.5281/zenodo.4491293.