paraview:fast#

Diverging color map (blue to red) with high discriminability and a smooth transition in the middle to prevent artifacts at the midpoint.

collection	category	license	authors	source
paraview	Diverging	BSD-3-Clause	Francesca Samsel, W. Alan Scott, Kenneth Moreland	https://github.com/kennethmoreland-com/kennethmoreland-com.github.io/tree/f0f50dcfda94c8e4c9c4927f78a98ff419fea450/content/color-advice/fast

cmapmatplotlibplotlynapariCSSMore...

from cmap import Colormap

cm = Colormap("paraview:fast")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("paraview:fast").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("paraview:fast").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("paraview:fast").to_napari())
napari.run()

background: #0E0E78;
background: linear-gradient(90deg, #0E0E78 0%, #1C2388 3.22581%, #263698 6.45161%, #2F49A8 9.67742%, #365CB8 12.9032%, #3C6FC9 16.129%, #4482D5 19.3548%, #4C94DE 22.5806%, #53A6E8 25.8065%, #5AB9F1 29.0323%, #6EC6F2 32.2581%, #84D2F0 35.4839%, #97DDED 38.7097%, #A9E9EB 41.9355%, #C1EEDF 45.1613%, #DAF0CD 48.3871%, #E9ECB8 51.6129%, #EFE1A0 54.8387%, #F3D788 58.0645%, #F3C977 61.2903%, #F1BB6A 64.5161%, #EFAC5C 67.7419%, #EC9D4F 70.9677%, #E58D46 74.1935%, #DD7E3D 77.4194%, #D66E34 80.6452%, #CE5E2B 83.871%, #C45027 87.0968%, #B84325 90.3226%, #AD3523 93.5484%, #A22621 96.7742%, #96141E 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("paraview:fast").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("paraview:fast").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("paraview:fast").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("paraview:fast").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("paraview:fast").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("paraview:fast").to_gee()
)

Perceptual lightness#

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

paraview:fast#

Perceptual lightness#

RGB components#

Hue & saturation#