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colorcet:CET_CBL2#

Aliases: colorcet:linear_protanopic_deuteranopic_kbw_5_98_c40_n256

Linear map with maximal chroma for Protanopic/Deuteranopic viewers

collection category license authors source
colorcet Sequential CC-BY-4.0 Peter Kovesi https://colorcet.com
from cmap import Colormap

cm = Colormap("colorcet:CET_CBL2")  # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_CBL2").to_mpl())
import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_CBL2").to_plotly())
import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_CBL2").to_napari())
napari.run()
background: #111111;
background: linear-gradient(90deg, #111111 0%, #15171F 3.22581%, #161D2D 6.45161%, #16233C 9.67742%, #152A4B 12.9032%, #12305A 16.129%, #103767 19.3548%, #0F3D74 22.5806%, #0F4480 25.8065%, #0F4B8D 29.0323%, #0E529A 32.2581%, #0D59A7 35.4839%, #0B61B4 38.7097%, #0868C2 41.9355%, #056FCF 45.1613%, #0177DD 48.3871%, #067FEA 51.6129%, #2786F2 54.8387%, #4F8EEE 58.0645%, #7595DB 61.2903%, #919DC2 64.5161%, #A7A5A8 67.7419%, #B9AD8F 70.9677%, #C9B576 74.1935%, #D7BD5C 77.4194%, #E4C53E 80.6452%, #EECD23 83.871%, #F7D634 87.0968%, #FDDE65 90.3226%, #FFE79C 93.5484%, #FEF0CD 96.7742%, #FCF9F3 100%);
import altair as alt
from cmap import Colormap

# df: a DataFrame with columns x, y and value
alt.Chart(df).mark_rect().encode(
    x="x:O",
    y="y:O",
    color=alt.Color(
        "value:Q", scale=alt.Scale(range=Colormap("colorcet:CET_CBL2").to_altair())
    ),
)
from bokeh.plotting import figure, show
from cmap import Colormap

p = figure()
p.image(
    image=[data], x=0, y=0, dw=1, dh=1,
    color_mapper=Colormap("colorcet:CET_CBL2").to_bokeh(),
)
show(p)
from vispy import app, scene
from cmap import Colormap

canvas = scene.SceneCanvas(show=True)
view = canvas.central_widget.add_view()
scene.visuals.Image(data, cmap=Colormap("colorcet:CET_CBL2").to_vispy(), parent=view.scene)
view.camera = scene.PanZoomCamera(aspect=1)
view.camera.set_range()
app.run()
import pygfx as gfx
from cmap import Colormap

image = gfx.Image(
    gfx.Geometry(grid=gfx.Texture(data, dim=2)),
    gfx.ImageBasicMaterial(
        clim=(data.min(), data.max()), map=Colormap("colorcet:CET_CBL2").to_pygfx()
    ),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_CBL2").to_pyqtgraph())
pg.exec()
import ee
from cmap import Colormap

ee.Initialize(project="my-project")  # your Google Cloud project
elevation = ee.Image("CGIAR/SRTM90_V4")
image = elevation.visualize(
    min=0, max=3000, palette=Colormap("colorcet:CET_CBL2").to_gee()
)

See also usage with external libraries.

colorcet:CET_CBL2colorcet:CET_CBL2 colormap
colorcet:CET_CBL2colorcet:CET_CBL2 colormap

Perceptual lightness#

Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)

RGB components#

Hue & saturation#