colorbrewer:Accent_8#
| collection | category | license | authors | source |
|---|---|---|---|---|
| colorbrewer | Qualitative | Apache-2.0 | Cynthia Brewer, Mark Harrower | https://github.com/axismaps/colorbrewer |
from cmap import Colormap
cm = Colormap("colorbrewer:Accent_8") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("colorbrewer:Accent_8").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("colorbrewer:Accent_8").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("colorbrewer:Accent_8").to_napari())
napari.run()
background: #7FC97F;
background: linear-gradient(90deg, #7FC97F 12.5%, #BEAED4 12.5%, #BEAED4 25%, #FDC086 25%, #FDC086 37.5%, #FFFF99 37.5%, #FFFF99 50%, #386CB0 50%, #386CB0 62.5%, #F0027F 62.5%, #F0027F 75%, #BF5B17 75%, #BF5B17 87.5%, #666666 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:Accent_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:Accent_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:Accent_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:Accent_8").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("colorbrewer:Accent_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:Accent_8").to_gee()
)
See also usage with external libraries.
colorbrewer:Accent_8
colorbrewer:Accent_8
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)