cmocean:ice#

The ice colormap is sequential from very dark blue (almost black) to very light blue (almost white). A use for this could be representations of sea ice.

collection	category	license	authors	source
cmocean	Sequential	MIT	Kristen M. Thyng	https://github.com/matplotlib/cmocean

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from cmap import Colormap

cm = Colormap("cmocean:ice")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("cmocean:ice").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("cmocean:ice").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("cmocean:ice").to_napari())
napari.run()

background: #040613;
background: linear-gradient(90deg, #040613 0%, #0B0D1E 3.22581%, #13142A 6.45161%, #1B1A36 9.67742%, #222143 12.9032%, #29274F 16.129%, #2F2D5C 19.3548%, #34346A 22.5806%, #393A78 25.8065%, #3C4185 29.0323%, #3E4992 32.2581%, #3F519D 35.4839%, #3E5AA6 38.7097%, #3E63AD 41.9355%, #3F6DB2 45.1613%, #4176B6 48.3871%, #447FB9 51.6129%, #4988BC 54.8387%, #4E90BF 58.0645%, #5599C2 61.2903%, #5CA2C5 64.5161%, #64ABC9 67.7419%, #6DB3CC 70.9677%, #77BCCF 74.1935%, #82C4D3 77.4194%, #8FCDD7 80.6452%, #9ED4DB 83.871%, #ADDCE0 87.0968%, #BDE4E7 90.3226%, #CCECEE 93.5484%, #DBF4F6 96.7742%, #EAFDFD 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("cmocean:ice").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("cmocean:ice").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("cmocean:ice").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("cmocean:ice").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("cmocean:ice").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("cmocean:ice").to_gee()
)

Perceptual lightness#

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

cmocean:ice#

Perceptual lightness#

RGB components#

Hue & saturation#