colorcet:CET_D13#
Aliases: colorcet:d13, colorcet:bwg, colorcet:diverging_bwg_20_95_c41_n256
Diverging blue - white - green 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_D13") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("colorcet:CET_D13").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_D13").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("colorcet:CET_D13").to_napari())
napari.run()
background: #112D68;
background: linear-gradient(90deg, #112D68 0%, #193779 3.22581%, #21428B 6.45161%, #294D9C 9.67742%, #2F59AE 12.9032%, #3466BE 16.129%, #3673CD 19.3548%, #3681DB 22.5806%, #3290E7 25.8065%, #369FF0 29.0323%, #48ADF7 32.2581%, #64BBFB 35.4839%, #83C7FB 38.7097%, #A3D3FA 41.9355%, #C3DEF7 45.1613%, #DCE8F2 48.3871%, #D9EAE6 51.6129%, #BCE3D7 54.8387%, #9ADAC7 58.0645%, #78D1B6 61.2903%, #59C6A4 64.5161%, #3EBA90 67.7419%, #2CAD7B 70.9677%, #24A065 74.1935%, #23934F 77.4194%, #21853E 80.6452%, #1C782F 83.871%, #166B23 87.0968%, #105E19 90.3226%, #095210 93.5484%, #034508 96.7742%, #003A02 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_D13").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_D13").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_D13").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_D13").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_D13").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_D13").to_gee()
)
See also usage with external libraries.
colorcet:CET_D13
colorcet:CET_D13
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)