colorblind

A colorblind-friendly python module that allows optimal color choice for plotting multiple curves
Works only with python 3
3 optimal colormaps are now available to map 2D fields
Version: 2.2.1 Author: Gaylor Wafflard-Fernandez
Author-email: gaylor.wafflard@univ-grenoble-alpes.fr

I. INSTALLATION
pip install cblind

II. USAGE FOR PLOTTING
import cblind as cb
5 palette functions for now
6 test plotting functions

color, linestyle = cb.Coloplots().cblind(nb_of_plots)
from 1 to 12 plots [DISTINCT COLORS]
For more than 12 plots, the linestyle is changed
cb.test_cblind(nb_of_plots)

color, linestyle = cb.Coloplots().contrast(nb_of_plots)
for less than 4 contrast plots [DISTINCT COLORS]
For more than 4 plots, the linestyle is changed
cb.test_contrast(nb_of_plots)

color, linestyle = cb.Coloplots().huescale(nb_of_plots, \*option)
from 1 to 9 plots [SEQUENTIAL DATA]
cb.test_huescale(nb_of_plots, \*option)
With option 'blue','bluegreen','green',
'gold','brown','rose','purple' for less than 3 plots, otherwise ocherscale

color, linestyle = cb.Coloplots().rbscale(nb_of_plots)
from 3 to 11 plots [DIVERGING DATA]
cb.test_rbscale(nb_of_plots)

color, linestyle = cb.Coloplots().solstice(nb_of_plots)
for less than 11 plots [DIVERGING DATA]
cb.test_solstice(nb_of_plots)

color, linestyle = cb.Coloplots().bird(nb_of_plots)
for less than 9 plots [DIVERGING DATA]
cb.test_bird(nb_of_plots)

color, linestyle = cb.Coloplots().pregunta(nb_of_plots)
for less than 9 plots [DIVERGING DATA]
cb.test_pregunta(nb_of_plots)

color, linestyle = cb.Coloplots().rainbow(nb_of_plots)
from 4 to 12 plots [RAINBOW SCHEME]
cb.test_rainbow(nb_of_plots)

color, linestyle = cb.Coloplots().monocolor(nb_of_plots, \*option)
from 1 to 13 plots [MONOCOLOR/PRINTING]
monochromatic but different linestyles cb.test_monocolor(nb_of_plots, \*option) With option "b&w", "blue", "red", "yellow", "green", "purple"

III. USAGE OF COLORMAPS
cmap = cb.cbmap(palette, nbin)
palette : 'rbscale', 'rainbow', 'huescale', 'solstice', 'bird', 'pregunta', 'iris', cf II., but also all colormaps from matplotlib + "_r" variants for reverse colormaps
nbin : discretization of the colormap
data2d : 2D field

a) Example, with a field data2d
import matplotlib.pyplot as plt

fig, ax = plt.subplots()
im=ax.imshow(data2d, cmap=cb.cbmap("rainbow_r", nbin=10), aspect='auto')
fig.colorbar(im)

fig, ax = plt.subplots()
im=ax.imshow(data2d, cmap=cb.cbmap("inferno"), aspect='auto') fig.colorbar(im)

b) Basic mapping functions

cb.mapping(fig,ax,data2d,extent,palette=palette,nbin=nbin)

cb.test_mapping(palette,nbin)

REFERENCE
Paul Tol. 2012. "Colour Schemes." SRON Technical Note, SRON/EPS/TN/09-002.
https://personal.sron.nl/~pault/data/colourschemes.pdf