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gnuplot:afmhot#

collection category license authors source
gnuplot Sequential gnuplot Thomas Williams, Colin Kelley http://www.gnuplot.info 
from cmap import Colormap

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

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #000000;
background: linear-gradient(90deg, #000000 0%, #100000 3.22581%, #210000 6.45161%, #310000 9.67742%, #420000 12.9032%, #520000 16.129%, #630000 19.3548%, #730000 22.5806%, #840400 25.8065%, #941500 29.0323%, #A52500 32.2581%, #B53500 35.4839%, #C54600 38.7097%, #D65600 41.9355%, #E66700 45.1613%, #F77700 48.3871%, #FF8808 51.6129%, #FF9819 54.8387%, #FFA929 58.0645%, #FFB93A 61.2903%, #FFCA4A 64.5161%, #FFDA5A 67.7419%, #FFEA6B 70.9677%, #FFFB7B 74.1935%, #FFFF8C 77.4194%, #FFFF9C 80.6452%, #FFFFAD 83.871%, #FFFFBD 87.0968%, #FFFFCE 90.3226%, #FFFFDE 93.5484%, #FFFFEF 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("gnuplot:afmhot").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:afmhot").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:afmhot").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:afmhot").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

See also usage with external libraries.

gnuplot:afmhotgnuplot:afmhot colormap
gnuplot:afmhotgnuplot:afmhot colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#