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matplotlib:nipy_spectral#

Contributed to matplotlib in 2006 by Tim Leslie from the nipy project.

collection category license authors source
matplotlib Miscellaneous PSF https://github.com/matplotlib/matplotlib 
from cmap import Colormap

cm = Colormap("matplotlib:nipy_spectral")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("matplotlib:nipy_spectral").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("matplotlib:nipy_spectral").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("matplotlib:nipy_spectral").to_napari())
napari.run()

background: #000000;
background: linear-gradient(90deg, #000000 0%, #770088 5%, #880099 10%, #0000AA 15%, #0000DD 20%, #0077DD 25%, #0099DD 30%, #00AAAA 35%, #00AA88 40%, #009900 45%, #00BB00 50%, #00DD00 55%, #00FF00 60%, #BBFF00 65%, #EEEE00 70%, #FFCC00 75%, #FF9900 80%, #FF0000 85%, #DD0000 90%, #CC0000 95%, #CCCCCC 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("matplotlib:nipy_spectral").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("matplotlib:nipy_spectral").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("matplotlib:nipy_spectral").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("matplotlib:nipy_spectral").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("matplotlib:nipy_spectral").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("matplotlib:nipy_spectral").to_gee()
)

See also usage with external libraries.

matplotlib:nipy_spectralmatplotlib:nipy_spectral colormap
matplotlib:nipy_spectralmatplotlib:nipy_spectral colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#