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cmasher:chroma#

The chroma colormap is a visual representation of all major colors.

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:chroma")  # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap

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

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

napari.imshow(data, colormap=Colormap("cmasher:chroma").to_napari())
napari.run()
background: #000000;
background: linear-gradient(90deg, #000000 0%, #010307 3.22581%, #010A1C 6.45161%, #021037 9.67742%, #100F57 12.9032%, #27056E 16.129%, #3B0175 19.3548%, #4C0276 22.5806%, #5D0274 25.8065%, #6D0270 29.0323%, #7E0168 32.2581%, #8E015E 35.4839%, #9D0751 38.7097%, #A91742 41.9355%, #B22833 45.1613%, #B83A25 48.3871%, #BB4C19 51.6129%, #BC5E0D 54.8387%, #BB6F03 58.0645%, #B78000 61.2903%, #B19107 64.5161%, #A7A216 67.7419%, #9AB225 70.9677%, #86C435 74.1935%, #65D54B 77.4194%, #2EE56A 80.6452%, #43ED92 83.871%, #7DF0B1 87.0968%, #A8F2CA 90.3226%, #CAF5DE 93.5484%, #E7F9F0 96.7742%, #FFFFFF 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:chroma").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:chroma").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:chroma").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:chroma").to_pygfx()
    ),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap

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

See also usage with external libraries.

cmasher:chromacmasher:chroma colormap
cmasher:chromacmasher:chroma colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#