TriSurface#
Download this notebook from GitHub (right-click to download).
- Title
- TriSurface Element
- Dependencies
- Matplotlib
- Backends
- Matplotlib
- Plotly
import numpy as np
import holoviews as hv
hv.extension('plotly')
The TriSurface
Element renders any collection of 3D points as a surface by applying Delaunay triangulation. It is therefore useful for plotting an arbitrary collection of datapoints as a 3D surface. Like other 3D elements it supports azimuth
, elevation
and distance
plot options to control the camera position:
y,x = np.mgrid[-5:5, -5:5] * 0.1
heights = np.sin(x**2+y**2)
trisurface = hv.TriSurface((x.flat,y.flat,heights.flat))
trisurface.opts(height=500, width=500)
Like all other colormapped plots we can easily add a colorbar
and control the cmap
of the plot:
u=np.linspace(0,2*np.pi, 24)
v=np.linspace(-1,1, 8)
u,v=np.meshgrid(u,v)
u=u.flatten()
v=v.flatten()
#evaluate the parameterization at the flattened u and v
tp=1+0.5*v*np.cos(u/2.)
x=tp*np.cos(u)
y=tp*np.sin(u)
z=0.5*v*np.sin(u/2.)
trisurface = hv.TriSurface((x, y, z), label='Moebius band')
trisurface.opts(cmap='fire', colorbar=True, height=500, width=500)
For full documentation and the available style and plot options, use hv.help(hv.TriSurface).
This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.
Download this notebook from GitHub (right-click to download).