gnuplot:rainbow#

collection	category	license	authors	source
gnuplot	Miscellaneous	gnuplot	Thomas Williams, Colin Kelley	http://www.gnuplot.info

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("gnuplot:rainbow")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("gnuplot:rainbow").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("gnuplot:rainbow").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("gnuplot:rainbow").to_napari())
napari.run()

background: #8000FF;
background: linear-gradient(90deg, #8000FF 0%, #6F1AFF 3.22581%, #5F33FE 6.45161%, #4E4CFC 9.67742%, #3E65FA 12.9032%, #2D7CF7 16.129%, #1D92F3 19.3548%, #0CA6EF 22.5806%, #04B9EA 25.8065%, #15CAE5 29.0323%, #25D8DF 32.2581%, #35E5D8 35.4839%, #46EFD1 38.7097%, #56F7CA 41.9355%, #67FCC1 45.1613%, #77FFB9 48.3871%, #88FFB0 51.6129%, #98FCA6 54.8387%, #A9F79C 58.0645%, #B9EF92 61.2903%, #CAE587 64.5161%, #DAD87C 67.7419%, #EACA70 70.9677%, #FBB965 74.1935%, #FFA659 77.4194%, #FF924C 80.6452%, #FF7C40 83.871%, #FF6533 87.0968%, #FF4C27 90.3226%, #FF331A 93.5484%, #FF1A0D 96.7742%, #FF0000 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("gnuplot:rainbow").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("gnuplot:rainbow").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("gnuplot:rainbow").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("gnuplot:rainbow").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("gnuplot:rainbow").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("gnuplot:rainbow").to_gee()
)

Perceptual lightness#

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

gnuplot:rainbow#

Perceptual lightness#

RGB components#

Hue & saturation#