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cmasher:dusk#

The dusk colormap is a visual representation of what the sky looks like during dusk (with the black/blue representing the dark sky and the orange/red the last few sunrays above the horizon).

collection category license authors source
cmasher Sequential BSD-3-Clause Ellert van der Velden https://github.com/1313e/CMasher
from cmap import Colormap

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

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

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

napari.imshow(data, colormap=Colormap("cmasher:dusk").to_napari())
napari.run()
background: #000000;
background: linear-gradient(90deg, #000000 0%, #020203 3.22581%, #05070E 6.45161%, #080F1B 9.67742%, #071727 12.9032%, #03202F 16.129%, #032832 19.3548%, #093033 22.5806%, #133634 25.8065%, #1D3D35 29.0323%, #274335 32.2581%, #314934 35.4839%, #3C4F32 38.7097%, #49542F 41.9355%, #56592C 45.1613%, #645C29 48.3871%, #726026 51.6129%, #816324 54.8387%, #906523 58.0645%, #9F6724 61.2903%, #AE6827 64.5161%, #BD692C 67.7419%, #CC6A33 70.9677%, #DB6B3C 74.1935%, #E86D4B 77.4194%, #EF7560 80.6452%, #F18174 83.871%, #F28D87 87.0968%, #F29A99 90.3226%, #F2A6AA 93.5484%, #F1B3BA 96.7742%, #F1BFCA 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("cmasher:dusk").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("cmasher:dusk").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("cmasher:dusk").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("cmasher:dusk").to_pygfx()
    ),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("cmasher:dusk").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("cmasher:dusk").to_gee()
)

See also usage with external libraries.

cmasher:duskcmasher:dusk colormap
cmasher:duskcmasher:dusk colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#