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colorcet:CET_D1#

Aliases: colorcet:d01, colorcet:d1, colorcet:bwr, colorcet:coolwarm, colorcet:diverging_bwr_40_95_c42_n256

Classic diverging blue - white - red colour map. End colours are matched in lightness and chroma

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

cm = Colormap("colorcet:CET_D1")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorcet:CET_D1").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_D1").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorcet:CET_D1").to_napari())
napari.run()

background: #2151DB;
background: linear-gradient(90deg, #2151DB 0%, #3F5ADD 3.22581%, #5363DE 6.45161%, #636DE0 9.67742%, #7276E2 12.9032%, #7F80E3 16.129%, #8C8AE5 19.3548%, #9794E6 22.5806%, #A39FE8 25.8065%, #AEA9E9 29.0323%, #B8B4EB 32.2581%, #C3BEEC 35.4839%, #CDC9ED 38.7097%, #D7D4EE 41.9355%, #E1DEEF 45.1613%, #EAE6ED 48.3871%, #F0E5E5 51.6129%, #F2DCD6 54.8387%, #F2CFC7 58.0645%, #F1C2B7 61.2903%, #EFB6A7 64.5161%, #EEA998 67.7419%, #EB9C89 70.9677%, #E88F7A 74.1935%, #E4826B 77.4194%, #E0755D 80.6452%, #DC674F 83.871%, #D75941 87.0968%, #D24B33 90.3226%, #CC3A25 93.5484%, #C62616 96.7742%, #C00206 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_D1").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_D1").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_D1").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_D1").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_D1").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_D1").to_gee()
)

See also usage with external libraries.

colorcet:CET_D1colorcet:CET_D1 colormap
colorcet:CET_D1colorcet:CET_D1 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#