seaborn:rocket#

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:rocket")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #03051A;
background: linear-gradient(90deg, #03051A 0%, #0D0A21 3.22581%, #19102A 6.45161%, #251432 9.67742%, #31183B 12.9032%, #3D1B43 16.129%, #4A1D49 19.3548%, #571E4F 22.5806%, #641F54 25.8065%, #721F57 29.0323%, #7F1E5A 32.2581%, #8D1D5B 35.4839%, #9B1B5B 38.7097%, #A9185A 41.9355%, #B71657 45.1613%, #C41852 48.3871%, #D01E4D 51.6129%, #DA2947 54.8387%, #E33641 58.0645%, #EA453E 61.2903%, #EE553F 64.5161%, #F16546 67.7419%, #F37450 70.9677%, #F4835B 74.1935%, #F59168 77.4194%, #F69F76 80.6452%, #F6AC85 83.871%, #F6B995 87.0968%, #F7C6A7 90.3226%, #F8D2B9 93.5484%, #F9DFCB 96.7742%, #FAEBDD 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:rocket").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:rocket").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:rocket").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:rocket").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

Perceptual lightness#

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

seaborn:rocket#

Perceptual lightness#

RGB components#

Hue & saturation#