yorick:earth#

Aliases: matplotlib:gist_earth, gist_earth

collection	category	license	authors	source
yorick	Miscellaneous	BSD-3-Clause	David Munro	https://github.com/LLNL/yorick

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("yorick:earth")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("yorick:earth").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("yorick:earth").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("yorick:earth").to_napari())
napari.run()

background: #000000;
background: linear-gradient(90deg, #000000 0%, #01002B 0.39%, #010038 0.78%, #05006E 2.75%, #050274 3.14%, #133078 10.98%, #1C4D7A 16.47%, #23627C 20.78%, #308080 28.24%, #459A49 45.88%, #4A9B46 46.67%, #69A34E 52.16%, #76A652 54.51%, #78A652 54.9%, #B7B75E 69.8%, #C0A465 78.43%, #C1A367 78.82%, #C2A46A 79.22%, #C4A46F 80%, #C6A574 80.78%, #C8A779 81.57%, #D7B298 86.67%, #D9B59D 87.45%, #DBB8A2 88.24%, #DEBBA7 89.02%, #DFBCAA 89.41%, #E0BDAD 89.8%, #ECD3CE 94.12%, #F1DCDA 95.69%, #F3E1E0 96.47%, #FCF8F8 99.61%, #FDFBFB 100%);

altairbokehvispypygfxpyqtgraphEarth Engine

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("yorick:earth").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("yorick:earth").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("yorick:earth").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("yorick:earth").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("yorick:earth").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("yorick:earth").to_gee()
)

Perceptual lightness#

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

yorick:earth#

Perceptual lightness#

RGB components#

Hue & saturation#