Subdivide Cells

Increase the number of triangles in a single, connected triangular mesh.

The pyvista.PolyDataFilters.subdivide() filter utilitizes three different subdivision algorithms to subdivide a mesh’s cells: butterfly, loop, or linear.

from pyvista import examples
import pyvista as pv

First, let’s load a triangulated mesh to subdivide. We can use the pyvista.DataSetFilters.triangulate() filter to ensure the mesh we are using is purely triangles.

mesh = examples.download_bunny_coarse().triangulate()

cpos = [(-0.02788175062966399, 0.19293295656233056, 0.4334449972621349),
 (-0.053260899930287015, 0.08881197167521734, -9.016948161029588e-05),
 (-0.10170607813337212, 0.9686438023715356, -0.22668272496584665)]

Now, lets do a few subdivisions with the mesh and compare the results. Below is a helper function to make a comparison plot of thee different subdivisions.

def plot_subdivisions(mesh, a, b):
    display_args = dict(show_edges=True, color=True)
    p = pv.Plotter(shape=(3,3))

    for i in range(3):
        p.subplot(i,0)
        p.add_mesh(mesh, **display_args)
        p.add_text("Original Mesh")

    def row_plot(row, subfilter):
        subs = [a, b]
        for i in range(2):
            p.subplot(row, i+1)
            p.add_mesh(mesh.subdivide(subs[i], subfilter=subfilter), **display_args)
            p.add_text("{} subdivision of {}".format(subfilter, subs[i]))
    row_plot(0, "linear")
    row_plot(1, "butterfly")
    row_plot(2, "loop")

    p.link_views()
    p.view_isometric()
    return p

Run the subdivisions for 1 and 3 levels.

plotter = plot_subdivisions(mesh, 1, 3)
plotter.camera_position = cpos
plotter.show()
subdivide

Out:

[(-0.02788175062966399, 0.19293295656233056, 0.4334449972621349),
 (-0.053260899930287015, 0.08881197167521734, -9.016948161029588e-05),
 (-0.10170607813337214, 0.9686438023715357, -0.22668272496584668)]

Total running time of the script: ( 0 minutes 3.635 seconds)

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