cetcolor
CET Perceptually Uniform Colour Maps
Collection of perceptually uniform colour maps made by Peter Kovesi
(2015) "Good Colour Maps: How to Design Them"
The cetcolor package is
designed to bring to R the 56 colour maps created by Peter
Kovesi that avoid points
of locally high colour contrast leading to the perception of false
anomalies in your data when there is none. The colour maps have been
designed to avoid this phenomenon by having uniform perceptual contrast
over their whole range.
Installation
The cetcolor package is available on both CRAN and GitHub. The CRAN
version is considered stable while the GitHub version is in a state of
development and may break.
You can install the stable version of the cetcolor package with:
install.packages("cetcolor")
For the development version, you can opt for:
install.packages("devtools")devtools::install_github("coatless/cetcolor")
Sample Usage
# Load the Librarylibrary("cetcolor")# Get RGB Hexadecimals for graphingcet_pal(5, name = "blues")#> [1] "#F1F1F1" "#C0D3EB" "#93B5DD" "#7197C1" "#3B7CB2"# Sample use with ggplot2library("ggplot2")ggplot(faithfuld, aes(waiting, eruptions)) +geom_raster(aes(fill = density)) +theme_bw() + theme(panel.grid=element_blank()) -> glibrary("gridExtra")# Frequently used colour maps have "nicknames" see ?cet_color_mapsgrid.arrange(g + scale_fill_gradientn(colours = cet_pal(5, name = "fire")),g + scale_fill_gradientn(colours = cet_pal(5, name = "inferno")),g + scale_fill_gradientn(colours = cet_pal(5, name = "blues")),g + scale_fill_gradientn(colours = cet_pal(5, name = "kgy")),ncol = 2, nrow = 2)
# Show a panel of possible values (without nicknames)display_cet_all()
References
CET
- CET Perceptually Uniform Colour Maps: Download
Page
- Location of CSV data, references, and data.
- colorcet for Python
- Shorthand naming of colour schemes and presentation of palettes
- PerceptualColourMaps.jl by Peter
Kovesi
- Referenced documentation and possible reimplementation of generation functions to avoid using CSV data.
R Colour Palettes
viridis(Source)- Provides MATLAB perceptually uniform colour maps in a manner that is similar to this package.
RColorBrewer(Source)- Function interface naming, e.g.
cet_pal(n, name), and colour map displays.
- Function interface naming, e.g.
scalesandggplot2- Proper ways to interface colour palettes with
ggplot2as shown forRColorBrewer.
- Proper ways to interface colour palettes with
Future
- Allow for n > 256.
- Provide hooks for ggplot2 gradient and discrete scales
- Port over the Peter’s generation code from Julia / MATLAB to R.
License
CC BY-SA 4.0
News
cetcolor 0.2.0
New
- Added new color maps to pre-existing types
- Linear
l3, long:linear_kryw_0-100_c71_n256l4, long:linear_kry_0-97_c73_n256l9, long:linear_bgyw_20-98_c66_n256l14, long:linear_ternary-green_0-46_c42_n256l16, long:linear_kbgyw_5-98_c62_n256l17, long:linear_worb_100-25_c53_n256l18, long:linear_wyor_100-45_c55_n256l19, long:linear_wcmr_100-45_c42_n256
- Divergent
d1a, long:diverging_bwr_20-95_c54_n256d13, long:diverging_bwg_20-95_c41_n256
- Linear
- Added new colourmap palettes for users with colour blindness
cbl1, long:linear-protanopic-deuteranopic_kbjyw_5-95_c25_n256cbl2, long:linear-protanopic-deuteranopic_kbw_5-98_c40_n256cbd1, long:diverging-protanopic-deuteranopic_bwy_60-95_c32_n256cbc1, long:cyclic-protanopic-deuteranopic_bwyk_16-96_c31_n256cbc2, long:cyclic-protanopic-deuteranopic_wywb_55-96_c33_n256cbtl1, long:linear-tritanopic_krjcw_5-98_c46_n256cbtl2, long:linear-tritanopic_krjcw_5-95_c24_n256cbtd1, long:diverging-tritanopic_cwr_75-98_c20_n256cbtc1, long:cyclic-tritanopic_cwrk_40-100_c20_n256cbtc2, long:cyclic-tritanopic_wrwc_70-100_c20_n256
- Added new naming scheme to access elements.
Changes
- Renamed old palettes to use the new shortnaming scheme. Please switch from
using the long palette names to the short names.
c1=cyclic_mrybm_35-75_c68_n256c1s=cyclic_mrybm_35-75_c68_n256_s25c2=cyclic_mygbm_30-95_c78_n256c2s=cyclic_mygbm_30-95_c78_n256_s25c4=cyclic_wrwbw_40-90_c42_n256c4s=cyclic_wrwbw_40-90_c42_n256_s25c5=cyclic_grey_15-85_c0_n256c5s=cyclic_grey_15-85_c0_n256_s25d1=diverging_bwr_40-95_c42_n256d2=diverging_gwv_55-95_c39_n256d3=diverging_gwr_55-95_c38_n256d4=diverging_bkr_55-10_c35_n256d6=diverging_bky_60-10_c30_n256d7=diverging-linear_bjy_30-90_c45_n256d8=diverging-linear_bjr_30-55_c53_n256d9=diverging_bwr_55-98_c37_n256d10=diverging_cwm_80-100_c22_n256d11=diverging-isoluminant_cjo_70_c25_n256d12=diverging-isoluminant_cjm_75_c23_n256r1=rainbow_bgyrm_35-85_c69_n256r2=rainbow_bgyr_35-85_c72_n256r3=diverging-rainbow_bgymr_45-85_c67_n256i1=isoluminant_cm_70_c39_n256i2=isoluminant_cgo_80_c38_n256i3=isoluminant_cgo_70_c39_n256l1=linear_grey_0-100_c0_n256l2=linear_grey_10-95_c0_n256l5=linear_green_5-95_c69_n256l6=linear_blue_5-95_c73_n256l7=linear_bmw_5-95_c86_n256l8=linear_bmy_10-95_c71_n256l10=linear_gow_60-85_c27_n256l11=linear_gow_65-90_c35_n256l12=linear_blue_95-50_c20_n256l13=linear_ternary-red_0-50_c52_n256l15=linear_ternary-blue_0-44_c57_n256
- Documentation switched from using Rd format to using Markdown in Roxygen2.
Deprecation
- Several of the initial color palettes have been deprecated. These palettes
will be phased out within the year. Please find a new palette.
diverging-isoluminant_cjm_75_c24_n256diverging-rainbow_bgymr_45-85_c67_n256diverging_gkr_60-10_c40_n256rainbow_bgyr_35-85_c73_n256rainbow_bgyrm_35-85_c71_n256linear_bgy_10-95_c74_n256linear_bgyw_15-100_c67_n256linear_bgyw_15-100_c68_n256linear_bmw_5-95_c89_n256linear_bmy_10-95_c78_n256linear_kry_5-95_c72_n256linear_kry_5-98_c75_n256linear_kryw_5-100_c64_n256linear_kryw_5-100_c67_n256linear_ternary-green_0-46_c42_n256
cetcolor 0.1.0
Features
- 51 perceptually uniform colour maps by Peter Kovesi
- Nicknamed frequently used colour maps.
- Colour map accessor functions similar to
RColorBrewer - Vignette displaying the colour maps within R.