gnuplot:ocean#

collection	category	license	authors	source
gnuplot	Miscellaneous	gnuplot	Thomas Williams, Colin Kelley	http://www.gnuplot.info

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("gnuplot:ocean")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("gnuplot:ocean").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("gnuplot:ocean").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("gnuplot:ocean").to_napari())
napari.run()

background: #008000;
background: linear-gradient(90deg, #008000 0%, #007308 3.22581%, #006710 6.45161%, #005A19 9.67742%, #004E21 12.9032%, #004229 16.129%, #003531 19.3548%, #00293A 22.5806%, #001D42 25.8065%, #00104A 29.0323%, #000452 32.2581%, #00085A 35.4839%, #001563 38.7097%, #00216B 41.9355%, #002D73 45.1613%, #003A7B 48.3871%, #004684 51.6129%, #00528C 54.8387%, #005F94 58.0645%, #006B9C 61.2903%, #0077A5 64.5161%, #0884AD 67.7419%, #2190B5 70.9677%, #3A9CBD 74.1935%, #52A9C5 77.4194%, #6BB5CE 80.6452%, #84C1D6 83.871%, #9CCEDE 87.0968%, #B5DAE6 90.3226%, #CEE6EF 93.5484%, #E6F3F7 96.7742%, #FFFFFF 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("gnuplot:ocean").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("gnuplot:ocean").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("gnuplot:ocean").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("gnuplot:ocean").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("gnuplot:ocean").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("gnuplot:ocean").to_gee()
)

Perceptual lightness#

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

gnuplot:ocean#

Perceptual lightness#

RGB components#

Hue & saturation#