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ibm:ibm_dark#

collection category license authors source
ibm Qualitative Apache-2.0 https://carbondesignsystem.com/data-visualization/color-palettes/#categorical-palettes 
from cmap import Colormap

cm = Colormap("ibm:ibm_dark")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("ibm:ibm_dark").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("ibm:ibm_dark").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("ibm:ibm_dark").to_napari())
napari.run()

background: #8A3FFC;
background: linear-gradient(90deg, #8A3FFC 7.14286%, #33B1FF 7.14286%, #33B1FF 14.2857%, #007D79 14.2857%, #007D79 21.4286%, #FF7EB6 21.4286%, #FF7EB6 28.5714%, #FA4D56 28.5714%, #FA4D56 35.7143%, #FFF1F1 35.7143%, #FFF1F1 42.8571%, #6FDC8C 42.8571%, #6FDC8C 50%, #4589FF 50%, #4589FF 57.1429%, #D12771 57.1429%, #D12771 64.2857%, #D2A106 64.2857%, #D2A106 71.4286%, #08BDBA 71.4286%, #08BDBA 78.5714%, #BAE6FF 78.5714%, #BAE6FF 85.7143%, #BA4E00 85.7143%, #BA4E00 92.8571%, #D4BBFF 92.8571%);

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("ibm:ibm_dark").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("ibm:ibm_dark").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("ibm:ibm_dark").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("ibm:ibm_dark").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("ibm:ibm_dark").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("ibm:ibm_dark").to_gee()
)

See also usage with external libraries.

ibm:ibm_darkibm:ibm_dark colormap
ibm:ibm_darkibm:ibm_dark colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#