Pointcloud density

"""Density plot from a distribution of points in 3D"""
from vedo import *
settings.default_backend = "vtk"

n = 3000
p = np.random.normal(7, 0.3, (n,3))
p[:int(n*1/3) ] += [1,0,0]       # shift 1/3 of the points along x by 1
p[ int(n*2/3):] += [1.7,0.4,0.2]

pts = Points(p, alpha=0.5)
pts

vedo.pointcloud.Points bounds (x/y/z) 5.941 ... 9.689 5.913 ... 8.431 5.936 ... 8.214 center of mass (7.89, 7.14, 7.07) average size 0.832 nr. points 3000

# Create a Volume from the points representing the points density
vol = pts.density(radius=0.25).cmap('Dark2').alpha([0.1,1])
vol.add_scalarbar3d(title='Density (counts in radius)', c='k')

PointDensity:   vedo.volume.Volume bounds (x/y/z) 5.941 ... 9.689 5.913 ... 8.431 5.936 ... 8.214 dimensions (40, 40, 40) voxel spacing (0.0961, 0.0646, 0.0584) in memory size 0MB point data array ImageScalars scalar range (0, 137.0)

show(pts, vol, __doc__, axes=1).close()