Skip to content

cmocean:tarn#

collection category license authors source
cmocean Diverging MIT Kristen M. Thyng https://github.com/matplotlib/cmocean 
from cmap import Colormap

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

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #17230E;
background: linear-gradient(90deg, #17230E 0%, #213210 3.22581%, #2C400F 6.45161%, #3B4C0D 9.67742%, #525615 12.9032%, #685F1C 16.129%, #7F6823 19.3548%, #96702B 22.5806%, #AF7833 25.8065%, #C78141 29.0323%, #D1925E 32.2581%, #D8A47B 35.4839%, #E0B797 38.7097%, #E8CBB4 41.9355%, #F1DED1 45.1613%, #FBF2ED 48.3871%, #FAF4EE 51.6129%, #EBE4D2 54.8387%, #DAD4B4 58.0645%, #C0C7A6 61.2903%, #A7BA9D 64.5161%, #8FAD96 67.7419%, #76A18E 70.9677%, #5D9587 74.1935%, #428981 77.4194%, #2A7B7D 80.6452%, #1F6C77 83.871%, #1B5D70 87.0968%, #154E6A 90.3226%, #0D3F64 93.5484%, #0A2F5E 96.7742%, #101E4F 100%);

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:tarn").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:tarn").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:tarn").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:tarn").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

See also usage with external libraries.

cmocean:tarncmocean:tarn colormap
cmocean:tarncmocean:tarn colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#