cmasher:ember#
The ember colormap is a visual representation of coal embers.
| collection | category | license | authors | source |
|---|---|---|---|---|
| cmasher | Sequential | BSD-3-Clause | Ellert van der Velden | https://github.com/1313e/CMasher |
from cmap import Colormap
cm = Colormap("cmasher:ember") # case insensitive
import matplotlib.pyplot as plt
from cmap import Colormap
plt.imshow(data, cmap=Colormap("cmasher:ember").to_mpl())
import plotly.express as px
from cmap import Colormap
px.imshow(data, color_continuous_scale=Colormap("cmasher:ember").to_plotly())
import napari
from cmap import Colormap
napari.imshow(data, colormap=Colormap("cmasher:ember").to_napari())
napari.run()
background: #000000;
background: linear-gradient(90deg, #000000 0%, #020204 3.22581%, #08070F 6.45161%, #130C1A 9.67742%, #1F1124 12.9032%, #2B152D 16.129%, #381734 19.3548%, #45193A 22.5806%, #531A3F 25.8065%, #601A42 29.0323%, #6E1945 32.2581%, #7C1746 35.4839%, #8B1445 38.7097%, #990F43 41.9355%, #A70B3E 45.1613%, #B40A38 48.3871%, #BF1231 51.6129%, #C91F29 54.8387%, #D22D21 58.0645%, #D93C1A 61.2903%, #DE4A13 64.5161%, #E3580C 67.7419%, #E86505 70.9677%, #EB7302 74.1935%, #EE8101 77.4194%, #F18E04 80.6452%, #F29B0C 83.871%, #F3A915 87.0968%, #F4B71F 90.3226%, #F3C429 93.5484%, #F2D233 96.7742%, #F1E13E 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("cmasher:ember").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("cmasher:ember").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("cmasher:ember").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("cmasher:ember").to_pygfx()
),
)
gfx.show(image)
import pyqtgraph as pg
from cmap import Colormap
view = pg.image(data)
view.setColorMap(Colormap("cmasher:ember").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("cmasher:ember").to_gee()
)
See also usage with external libraries.
cmasher:ember
cmasher:ember
Perceptual lightness#
Lightness (J′) measured in CAM02 Uniform Color Space (CAM02-UCS)