tol:rainbow_discrete_16#
| collection | category | license | authors | source |
|---|---|---|---|---|
| tol | Miscellaneous | BSD-3-Clause | Paul Tol | https://personal.sron.nl/~pault/ |
from cmap import Colormap
cm = Colormap("tol:rainbow_discrete_16") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("tol:rainbow_discrete_16").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("tol:rainbow_discrete_16").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("tol:rainbow_discrete_16").to_napari())
napari.run()
background: #D1BBD7;
background: linear-gradient(90deg, #D1BBD7 6.25%, #BA8DB4 6.25%, #BA8DB4 12.5%, #AA6F9E 12.5%, #AA6F9E 18.75%, #882E72 18.75%, #882E72 25%, #1965B0 25%, #1965B0 31.25%, #5289C7 31.25%, #5289C7 37.5%, #7BAFDE 37.5%, #7BAFDE 43.75%, #4EB265 43.75%, #4EB265 50%, #90C987 50%, #90C987 56.25%, #CAE0AB 56.25%, #CAE0AB 62.5%, #F7F056 62.5%, #F7F056 68.75%, #F6C141 68.75%, #F6C141 75%, #F1932D 75%, #F1932D 81.25%, #E8601C 81.25%, #E8601C 87.5%, #DC050C 87.5%, #DC050C 93.75%, #72190E 93.75%);
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("tol:rainbow_discrete_16").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("tol:rainbow_discrete_16").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("tol:rainbow_discrete_16").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("tol:rainbow_discrete_16").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("tol:rainbow_discrete_16").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("tol:rainbow_discrete_16").to_gee()
)
See also usage with external libraries.
tol:rainbow_discrete_16
tol:rainbow_discrete_16
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)