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colorcet:CET_C8#

Aliases: colorcet:cyclic_mygbm_50_90_c46_n256

Cyclic: low contrast colour ellipse

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

cm = Colormap("colorcet:CET_C8")  # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_C8").to_mpl())
import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_C8").to_plotly())
import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_C8").to_napari())
napari.run()
background: #E99495;
background: linear-gradient(90deg, #E99495 0%, #ED9D8C 3.22581%, #F0A783 6.45161%, #F0B17A 9.67742%, #EDBB72 12.9032%, #EAC56B 16.129%, #E3CF65 19.3548%, #D9D861 22.5806%, #C8DF65 25.8065%, #B5DF71 29.0323%, #A3DC7F 32.2581%, #92D88D 35.4839%, #80D399 38.7097%, #6ECDA5 41.9355%, #5CC7B1 45.1613%, #48C0BC 48.3871%, #35B9C5 51.6129%, #20B1CE 54.8387%, #0CA9D6 58.0645%, #04A1DC 61.2903%, #1299E2 64.5161%, #2590E7 67.7419%, #3C87EA 70.9677%, #597EE9 74.1935%, #7C78E2 77.4194%, #9777D7 80.6452%, #AC78CC 83.871%, #BD7BC1 87.0968%, #CB7FB6 90.3226%, #D785AB 93.5484%, #E18BA1 96.7742%, #E89397 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_C8").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_C8").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_C8").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_C8").to_pygfx()
    ),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_C8").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_C8").to_gee()
)

See also usage with external libraries.

colorcet:CET_C8colorcet:CET_C8 colormap
colorcet:CET_C8colorcet:CET_C8 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#