Delaunay triangulation from voronoi tessellation

Hello @marcomusy, I would like to know how Delaunay triangulation can be applied to find the connectivity of the cells formed by voronoi tessellation in vedo.

The following is the code that I’m using to generate voronoi cells using the scipy library. I’d like to do this in vedo but I am not sure how to do it.

    import numpy as np
    from scipy.spatial import Voronoi, voronoi_plot_2d
    import shapely.geometry
    import shapely.ops
    
    points = np.random.random((20, 2))
    vor = Voronoi(points)
    fig = voronoi_plot_2d(vor)
    plt.show()

I would like to know if voronoi tessellation can be generated in vedo and find the cell connectivity by applying Delaunay triangulation. Here, I am actually looking at applying this to biological cells to find how the biological cells are connected with each other.

Thanks a lot

[marcomusy]

Not an expert… I guess you can overlay the DT with delaunay2D, which is the “dual” of voronoi, and then use examples/basic/connVtx.py to link the voronoi cells. You maybe still left with the problem that triangulation is a bit arbitrary, so you may end up with different connectivity matrices for very similar point configurations.

[marcomusy]

simply replace .wireframe(False)