cmocean:algae#

The algae colormap is sequential with whitish-green for low values and increasing in green with increasing value, which could be used to represent an increase in chlorophyll in the water. This colormap is based on Greens, but was recreated from scratch using the viscm tool.

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

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

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

import matplotlib.pyplot as plt
from cmap import Colormap

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

import plotly.express as px
from cmap import Colormap

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

import napari
from cmap import Colormap

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

background: #D7F9D0;
background: linear-gradient(90deg, #D7F9D0 0%, #CDF2C4 3.22581%, #C2EAB8 6.45161%, #B8E3AC 9.67742%, #ADDCA1 12.9032%, #A3D596 16.129%, #98CF8C 19.3548%, #8DC881 22.5806%, #81C278 25.8065%, #75BC6E 29.0323%, #69B666 32.2581%, #5AB05E 35.4839%, #4BAB57 38.7097%, #39A553 41.9355%, #279F51 45.1613%, #189851 48.3871%, #0D914F 51.6129%, #07894E 54.8387%, #07824C 58.0645%, #0B7A4A 61.2903%, #0F7347 64.5161%, #136C44 67.7419%, #166440 70.9677%, #185D3C 74.1935%, #195638 77.4194%, #1A4F33 80.6452%, #1A472F 83.871%, #19402A 87.0968%, #183925 90.3226%, #16321F 93.5484%, #142B1A 96.7742%, #122414 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:algae").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:algae").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:algae").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:algae").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

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

Perceptual lightness#

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

cmocean:algae#

Perceptual lightness#

RGB components#

Hue & saturation#