matplotlib:twilight#

collection	category	license	authors	source
matplotlib	Cyclic	PSF	Bastian Bechtold	https://github.com/matplotlib/matplotlib

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("matplotlib:twilight")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("matplotlib:twilight").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("matplotlib:twilight").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("matplotlib:twilight").to_napari())
napari.run()

background: #E2D9E2;
background: linear-gradient(90deg, #E2D9E2 0%, #D6D7DC 3.22581%, #C1CDD3 6.45161%, #A8C1CB 9.67742%, #91B3C6 12.9032%, #7EA4C3 16.129%, #7094C0 19.3548%, #6683BD 22.5806%, #6171B9 25.8065%, #5F5EB3 29.0323%, #5E4AA9 32.2581%, #5C369B 35.4839%, #572487 38.7097%, #4D176C 41.9355%, #3F1251 45.1613%, #34113D 48.3871%, #341238 51.6129%, #42123E 54.8387%, #561547 58.0645%, #6C1B4E 61.2903%, #812350 64.5161%, #933050 67.7419%, #A24050 70.9677%, #AF5151 74.1935%, #B96456 77.4194%, #C17860 80.6452%, #C78C6F 83.871%, #CBA085 87.0968%, #D1B49F 90.3226%, #D8C5BB 93.5484%, #DED3D4 96.7742%, #E2D9E2 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("matplotlib:twilight").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("matplotlib:twilight").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("matplotlib:twilight").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("matplotlib:twilight").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("matplotlib:twilight").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("matplotlib:twilight").to_gee()
)

Perceptual lightness#

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

matplotlib:twilight#

Perceptual lightness#

RGB components#

Hue & saturation#