cmasher:neon#

The neon colormap is a visual representation of the typical neon signs found in leisure areas.

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

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("cmasher:neon")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("cmasher:neon").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("cmasher:neon").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("cmasher:neon").to_napari())
napari.run()

background: #A70C03;
background: linear-gradient(90deg, #A70C03 0%, #AC0E20 3.22581%, #B11036 6.45161%, #B6104C 9.67742%, #BB0E63 12.9032%, #BF0A7A 16.129%, #C30692 19.3548%, #C606AB 22.5806%, #C612C3 25.8065%, #C424D8 29.0323%, #BE38E8 32.2581%, #B74BF3 35.4839%, #AD5DF9 38.7097%, #A26DFC 41.9355%, #977BFD 45.1613%, #8A88FD 48.3871%, #7D94FC 51.6129%, #6E9FF9 54.8387%, #5DA9F6 58.0645%, #4BB3F0 61.2903%, #38BCE9 64.5161%, #25C4E1 67.7419%, #13CBD8 70.9677%, #0BD2CE 74.1935%, #13D9C3 77.4194%, #21DFB7 80.6452%, #30E5A9 83.871%, #41EB98 87.0968%, #52F185 90.3226%, #65F66D 93.5484%, #79FA4E 96.7742%, #8EFE15 100%);

altairbokehvispypygfxpyqtgraphEarth Engine

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:neon").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:neon").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:neon").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:neon").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

Perceptual lightness#

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

cmasher:neon#

Perceptual lightness#

RGB components#

Hue & saturation#