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cmasher:voltage#

The voltage colormap is a visual representation of the high voltage electricity in a tesla coil or lightning strike.

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:voltage")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #000000;
background: linear-gradient(90deg, #000000 0%, #040203 3.22581%, #10060D 6.45161%, #1D0B18 9.67742%, #2A0F24 12.9032%, #361330 16.129%, #43143E 19.3548%, #50154E 22.5806%, #5C1360 25.8065%, #681074 29.0323%, #720E8A 32.2581%, #7A11A0 35.4839%, #7F1CB4 38.7097%, #822AC5 41.9355%, #833AD4 45.1613%, #8349E0 48.3871%, #8159EA 51.6129%, #7D67F1 54.8387%, #7976F7 58.0645%, #7584FC 61.2903%, #7192FE 64.5161%, #6E9FFE 67.7419%, #70ACFC 70.9677%, #77B7F9 74.1935%, #84C1F5 77.4194%, #95CBF1 80.6452%, #A7D3F0 83.871%, #B9DCF0 87.0968%, #CBE4F1 90.3226%, #DDEDF5 93.5484%, #EEF6F9 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:voltage").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:voltage").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:voltage").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:voltage").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

See also usage with external libraries.

cmasher:voltagecmasher:voltage colormap
cmasher:voltagecmasher:voltage colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#