colorcet:CET_C11#
Aliases: colorcet:cyclic_bgrmb_35_70_c75_n256
Cyclic: blue - green - red - magenta. Allows four orientations/phase angles to be visulaised.
| collection | category | license | authors | source |
|---|---|---|---|---|
| colorcet | Cyclic | CC-BY-4.0 | Peter Kovesi | https://colorcet.com |
from cmap import Colormap
cm = Colormap("colorcet:CET_C11") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("colorcet:CET_C11").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("colorcet:CET_C11").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("colorcet:CET_C11").to_napari())
napari.run()
background: #4731F2;
background: linear-gradient(90deg, #4731F2 0%, #5142E1 3.22581%, #6157CA 6.45161%, #696CB3 9.67742%, #6B7F9C 12.9032%, #679183 16.129%, #5CA369 19.3548%, #4CB34C 22.5806%, #4AB72E 25.8065%, #61AD1A 29.0323%, #789C10 32.2581%, #898909 35.4839%, #967503 38.7097%, #A06000 41.9355%, #A74700 45.1613%, #AF2807 48.3871%, #BA071B 51.6129%, #C70835 54.8387%, #D41E52 58.0645%, #E02F70 61.2903%, #EB3E8F 64.5161%, #F44CAF 67.7419%, #FB59D0 70.9677%, #FC62ED 74.1935%, #F061FC 77.4194%, #DD58FF 80.6452%, #C74FFE 83.871%, #B045FD 87.0968%, #983CFC 90.3226%, #7D33FB 93.5484%, #5E2DF9 96.7742%, #4830F3 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_C11").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_C11").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_C11").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_C11").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("colorcet:CET_C11").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_C11").to_gee()
)
See also usage with external libraries.
colorcet:CET_C11
colorcet:CET_C11
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)