crameri:fes#
| collection | category | license | authors | source |
|---|---|---|---|---|
| crameri | Miscellaneous | MIT | Fabio Crameri | https://zenodo.org/record/5501399 |
from cmap import Colormap
cm = Colormap("crameri:fes") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("crameri:fes").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("crameri:fes").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("crameri:fes").to_napari())
napari.run()
background: #0D0D0D;
background: linear-gradient(90deg, #0D0D0D 0%, #1D1D1D 3.22581%, #2C2C2C 6.45161%, #3A3A3A 9.67742%, #484848 12.9032%, #555555 16.129%, #626262 19.3548%, #6E6E6E 22.5806%, #797979 25.8065%, #858585 29.0323%, #929292 32.2581%, #A0A0A0 35.4839%, #B0B0B0 38.7097%, #C1C1C1 41.9355%, #D3D3D3 45.1613%, #E8E8E8 48.3871%, #0E4424 51.6129%, #274D20 54.8387%, #405621 58.0645%, #555B24 61.2903%, #696028 64.5161%, #7C652C 67.7419%, #906B30 70.9677%, #A47339 74.1935%, #B5814B 77.4194%, #C09364 80.6452%, #C7A67E 83.871%, #CFB899 87.0968%, #D7C9B5 90.3226%, #DFD7CE 93.5484%, #E6E1E4 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:fes").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:fes").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:fes").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:fes").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("crameri:fes").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:fes").to_gee()
)
See also usage with external libraries.
crameri:fes
crameri:fes
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)