Skip to content

colorcet:CET_L18#

Aliases: colorcet:l18, colorcet:linear_wyor_100_45_c55_n256, colorcet:wyor

White-Yellow-Orange-Red, decreasing lightness with increasing saturation

collection category license authors source
colorcet Sequential CC-BY-4.0 Peter Kovesi https://colorcet.com 
from cmap import Colormap

cm = Colormap("colorcet:CET_L18")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_L18").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_L18").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_L18").to_napari())
napari.run()

background: #FFFFFF;
background: linear-gradient(90deg, #FFFFFF 0%, #FAFBEA 3.22581%, #F5F8D4 6.45161%, #F0F4C1 9.67742%, #EEEEB4 12.9032%, #EBE9A8 16.129%, #E9E39C 19.3548%, #E8DD91 22.5806%, #E7D886 25.8065%, #E6D17C 29.0323%, #E6CB72 32.2581%, #E5C569 35.4839%, #E5BE60 38.7097%, #E4B857 41.9355%, #E4B14F 45.1613%, #E4AA48 48.3871%, #E3A341 51.6129%, #E39C39 54.8387%, #E39534 58.0645%, #E28E2E 61.2903%, #E28628 64.5161%, #E17F24 67.7419%, #E07720 70.9677%, #E06F1D 74.1935%, #DF671B 77.4194%, #DE5E19 80.6452%, #DD5519 83.871%, #DB4B19 87.0968%, #DA4019 90.3226%, #D8341A 93.5484%, #D7261C 96.7742%, #D50F1D 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("colorcet:CET_L18").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("colorcet:CET_L18").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("colorcet:CET_L18").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("colorcet:CET_L18").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_L18").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("colorcet:CET_L18").to_gee()
)

See also usage with external libraries.

colorcet:CET_L18colorcet:CET_L18 colormap
colorcet:CET_L18colorcet:CET_L18 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#