crameri:bukavu#
| collection | category | license | authors | source |
|---|---|---|---|---|
| crameri | Miscellaneous | MIT | Fabio Crameri | https://zenodo.org/record/5501399 |
from cmap import Colormap
cm = Colormap("crameri:bukavu") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("crameri:bukavu").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("crameri:bukavu").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("crameri:bukavu").to_napari())
napari.run()
background: #1A3333;
background: linear-gradient(90deg, #1A3333 0%, #1C3A43 3.22581%, #1E4256 6.45161%, #204C6D 9.67742%, #245989 12.9032%, #29689F 16.129%, #2E77B2 19.3548%, #3486C3 22.5806%, #4395C8 25.8065%, #52A3C9 29.0323%, #61B1CA 32.2581%, #70BECB 35.4839%, #81CBCD 38.7097%, #9CDAD3 41.9355%, #BBEADB 45.1613%, #D7F8E2 48.3871%, #044423 51.6129%, #0F4F1A 54.8387%, #225D13 58.0645%, #3E6916 61.2903%, #5A7020 64.5161%, #70752C 67.7419%, #847835 70.9677%, #967C3F 74.1935%, #A8834E 77.4194%, #B99265 80.6452%, #C4A47F 83.871%, #CDB799 87.0968%, #D6C8B5 90.3226%, #DFD6CE 93.5484%, #E6E2E5 96.7742%, #EDEDFC 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("crameri:bukavu").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("crameri:bukavu").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("crameri:bukavu").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("crameri:bukavu").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("crameri:bukavu").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("crameri:bukavu").to_gee()
)
See also usage with external libraries.
crameri:bukavu
crameri:bukavu
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)