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colorbrewer:Reds_8#

collection category license authors source
colorbrewer Sequential Apache-2.0 Cynthia Brewer, Mark Harrower https://github.com/axismaps/colorbrewer 
from cmap import Colormap

cm = Colormap("colorbrewer:Reds_8")  # case insensitive

import matplotlib.pyplot as plt
from cmap import Colormap

plt.imshow(data, cmap=Colormap("colorbrewer:Reds_8").to_mpl())

import plotly.express as px
from cmap import Colormap

px.imshow(data, color_continuous_scale=Colormap("colorbrewer:Reds_8").to_plotly())

import napari
from cmap import Colormap

napari.imshow(data, colormap=Colormap("colorbrewer:Reds_8").to_napari())
napari.run()

background: #FFF5F0;
background: linear-gradient(90deg, #FFF5F0 12.5%, #FEE0D2 12.5%, #FEE0D2 25%, #FCBBA1 25%, #FCBBA1 37.5%, #FC9272 37.5%, #FC9272 50%, #FB6A4A 50%, #FB6A4A 62.5%, #EF3B2C 62.5%, #EF3B2C 75%, #CB181D 75%, #CB181D 87.5%, #99000D 87.5%);

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("colorbrewer:Reds_8").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("colorbrewer:Reds_8").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("colorbrewer:Reds_8").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("colorbrewer:Reds_8").to_pygfx()
    ),
)
gfx.show(image)

import pyqtgraph as pg
from cmap import Colormap

view = pg.image(data)
view.setColorMap(Colormap("colorbrewer:Reds_8").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("colorbrewer:Reds_8").to_gee()
)

See also usage with external libraries.

colorbrewer:Reds_8colorbrewer:Reds_8 colormap
colorbrewer:Reds_8colorbrewer:Reds_8 colormap

Perceptual lightness#

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

RGB components#

Hue & saturation#