imagej:ice#

collection	category	license	authors	source
imagej	Miscellaneous	BSD-2-Clause		https://github.com/imagej/imagej-common

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

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

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #009C8C;
background: linear-gradient(90deg, #009C8C 0%, #00A593 3.22581%, #00B09E 6.45161%, #00B8A6 9.67742%, #00BEAA 12.9032%, #00C4B0 16.129%, #13C1D1 19.3548%, #1DB8DC 22.5806%, #32ABEA 25.8065%, #30A2E1 29.0323%, #4F92EC 32.2581%, #707DF6 35.4839%, #866BFA 38.7097%, #9E5DFB 41.9355%, #BA51FA 45.1613%, #C957FA 48.3871%, #D95CF5 51.6129%, #E561E6 54.8387%, #F25FE6 58.0645%, #FA5DDE 61.2903%, #FA5DCA 64.5161%, #FA5AB4 67.7419%, #FA55A3 70.9677%, #FB458E 74.1935%, #FA407B 77.4194%, #FA3672 80.6452%, #FA2F6A 83.871%, #FA235E 87.0968%, #FB1354 90.3226%, #FB0040 93.5484%, #F3041A 96.7742%, #E6001B 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("imagej: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("imagej: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("imagej: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("imagej:ice").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

Perceptual lightness#

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

imagej:ice#

Perceptual lightness#

RGB components#

Hue & saturation#