colorcet:CET_D11#
Aliases: colorcet:d11, colorcet:diverging_isoluminant_cjo_70_c25_n256
Diverging isoluminant lightblue - lightgrey - orange colour map
| collection | category | license | authors | source |
|---|---|---|---|---|
| colorcet | Diverging | CC-BY-4.0 | Peter Kovesi | https://colorcet.com |
from cmap import Colormap
cm = Colormap("colorcet:CET_D11") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("colorcet:CET_D11").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_D11").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("colorcet:CET_D11").to_napari())
napari.run()
background: #00B6FF;
background: linear-gradient(90deg, #00B6FF 0%, #25B6FD 3.22581%, #3FB5F7 6.45161%, #50B4F1 9.67742%, #5DB3EC 12.9032%, #68B3E6 16.129%, #72B2E0 19.3548%, #7AB1DB 22.5806%, #82B0D5 25.8065%, #89B0CF 29.0323%, #8FAFCA 32.2581%, #95AEC4 35.4839%, #9AAEBF 38.7097%, #A0ADB9 41.9355%, #A4ACB3 45.1613%, #A9ABAE 48.3871%, #AEAAA9 51.6129%, #B4A9A5 54.8387%, #BAA7A1 58.0645%, #C0A69D 61.2903%, #C5A499 64.5161%, #CAA395 67.7419%, #CFA191 70.9677%, #D49F8D 74.1935%, #D99D89 77.4194%, #DD9C85 80.6452%, #E29A81 83.871%, #E6987D 87.0968%, #EA9679 90.3226%, #EE9475 93.5484%, #F29271 96.7742%, #F6906D 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_D11").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_D11").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_D11").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_D11").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_D11").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_D11").to_gee()
)
See also usage with external libraries.
colorcet:CET_D11
colorcet:CET_D11
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)