seaborn:crest#

collection	category	license	authors	source
seaborn	Sequential	BSD-3-Clause	Michael Waskom	https://github.com/mwaskom/seaborn

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("seaborn:crest")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("seaborn:crest").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("seaborn:crest").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("seaborn:crest").to_napari())
napari.run()

background: #A5CD90;
background: linear-gradient(90deg, #A5CD90 0%, #9CC891 3.22581%, #93C491 6.45161%, #8AC091 9.67742%, #80BB91 12.9032%, #77B791 16.129%, #6FB390 19.3548%, #66AE90 22.5806%, #5FA990 25.8065%, #58A590 29.0323%, #52A090 32.2581%, #4C9B90 35.4839%, #46968F 38.7097%, #41918F 41.9355%, #3C8C8E 45.1613%, #36888D 48.3871%, #31838D 51.6129%, #2C7E8C 54.8387%, #27798C 58.0645%, #22748B 61.2903%, #1F6F8A 64.5161%, #1D6A8A 67.7419%, #1C6588 70.9677%, #1D5F87 74.1935%, #1F5A85 77.4194%, #215483 80.6452%, #244E81 83.871%, #26497E 87.0968%, #28437B 90.3226%, #2A3D77 93.5484%, #2B3774 96.7742%, #2C3172 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("seaborn:crest").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("seaborn:crest").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("seaborn:crest").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("seaborn:crest").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("seaborn:crest").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("seaborn:crest").to_gee()
)

Perceptual lightness#

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

seaborn:crest#

Perceptual lightness#

RGB components#

Hue & saturation#