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- """Density plot from a distribution of points in 2D"""
- import numpy as np
- from vedo import *
- settings.use_depth_peeling = True
- n = 10000
- p = np.random.normal(0, 0.3, (n,2))
- p[:int(n*1/3) ] += [1.0, 0.0] # shift 1/3 of the points along x by 1
- p[ int(n*2/3):] += [1.7, 0.4]
- # create the point cloud
- pts = Points(p).color('k', 0.2)
- # radius of local search can be specified (None=automatic)
- vol = pts.density(radius=None).cmap('Paired_r') # returns a Volume
- # Other cool color mapping: Set1_r, Dark2. Or you can build your own, e.g.:
- # vol.c(['w','w','y','y','r','r','g','g','b','k']).alpha([0,1])
- r = precision(vol.metadata['radius'], 2) # retrieve automatic radius value
- vol.add_scalarbar3d(title='Density (counts in r_search ='+r+')', c='k', italic=1)
- show([(pts,__doc__), vol], N=2, axes=True).close()
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