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colorcet:CET_L2#

Aliases: colorcet:l02, colorcet:l2, colorcet:linear_grey_10_95_c0_n256, colorcet:reducedgrey

Grey scale with slightly reduced contrast to avoid display saturation problems

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

cm = Colormap("colorcet:CET_L2")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_L2").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_L2").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_L2").to_napari())
napari.run()

background: #1B1B1B;
background: linear-gradient(90deg, #1B1B1B 0%, #212121 3.22581%, #272727 6.45161%, #2C2C2C 9.67742%, #323232 12.9032%, #383838 16.129%, #3F3F3F 19.3548%, #454545 22.5806%, #4B4B4B 25.8065%, #525252 29.0323%, #585858 32.2581%, #5F5F5F 35.4839%, #656565 38.7097%, #6C6C6C 41.9355%, #737373 45.1613%, #7A7A7A 48.3871%, #818181 51.6129%, #888888 54.8387%, #8F8F8F 58.0645%, #969696 61.2903%, #9D9D9D 64.5161%, #A5A5A5 67.7419%, #ACACAC 70.9677%, #B3B3B3 74.1935%, #BBBBBB 77.4194%, #C2C2C2 80.6452%, #CACACA 83.871%, #D2D2D2 87.0968%, #D9D9D9 90.3226%, #E1E1E1 93.5484%, #E9E9E9 96.7742%, #F1F1F1 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_L2").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_L2").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_L2").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_L2").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_L2").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_L2").to_gee()
)

See also usage with external libraries.

colorcet:CET_L2colorcet:CET_L2 colormap
colorcet:CET_L2colorcet:CET_L2 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#