Skip to content

colorcet:CET_L16#

Aliases: colorcet:l16, colorcet:kbgyw, colorcet:linear_kbgyw_10_98_c63_n256

Black-Blue-Green-Yellow-White colour map

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

cm = Colormap("colorcet:CET_L16")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_L16").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_L16").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_L16").to_napari())
napari.run()

background: #1B1B1B;
background: linear-gradient(90deg, #1B1B1B 0%, #261B3F 3.22581%, #291960 6.45161%, #26197F 9.67742%, #1F1B98 12.9032%, #1321AA 16.129%, #092BB4 19.3548%, #0737B7 22.5806%, #0742B8 25.8065%, #074DB6 29.0323%, #0759B1 32.2581%, #0864A7 35.4839%, #176F9A 38.7097%, #247989 41.9355%, #2C8376 45.1613%, #308D61 48.3871%, #34974D 51.6129%, #3D9F3C 54.8387%, #4AA72E 58.0645%, #5BAE21 61.2903%, #6DB514 64.5161%, #80BB08 67.7419%, #94C103 70.9677%, #A8C603 74.1935%, #BBCB08 77.4194%, #CCD111 80.6452%, #DCD71C 83.871%, #EADD2A 87.0968%, #F4E43B 90.3226%, #F9ED5A 93.5484%, #FFF494 96.7742%, #F9F9F9 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_L16").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_L16").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_L16").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_L16").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_L16").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_L16").to_gee()
)

See also usage with external libraries.

colorcet:CET_L16colorcet:CET_L16 colormap
colorcet:CET_L16colorcet:CET_L16 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#