Volume Smoothing

Smoothing rough edges of a volumetric surface

# sphinx_gallery_thumbnail_number = 4
import pyvista as pv
from pyvista import examples

Suppose you extract a volumetric subset of a dataset that has roughly defined edges. Perhaps you’d like a smooth representation of that model region. This can be achieved by extracting the bounding surface of the volume and applying a pyvista.PolyData.smooth() filter.

The below code snippet loads a sample roughly edged volumetric dataset:

# Vector to view rough edges
cpos = [-2, 5, 3]

# Load dataset
data = examples.load_uniform()
# Extract a rugged volume
vol = data.threshold_percent(30, invert=1)
vol.plot(show_edges=True, cpos=cpos)
../../_images/sphx_glr_volume-smoothing_001.png

Extract the outer surface of the volume using the pyvista.DataSetFilters.extract_geometry() filter and then apply the smoothing filter:

# Get the out surface as PolyData
surf = vol.extract_geometry()
# Smooth the surface
smooth = surf.smooth()
smooth.plot(show_edges=True, cpos=cpos)
../../_images/sphx_glr_volume-smoothing_002.png

Not smooth enough? Try increasing the number of iterations for the Laplacian smoothing algorithm:

# Smooth the surface even more
smooth = surf.smooth(n_iter=100)
smooth.plot(show_edges=True, cpos=cpos)
../../_images/sphx_glr_volume-smoothing_003.png

Still not smooth enough? Increase the number of iterations for the Laplacian smoothing algorithm to a crazy high value:

# Smooth the surface EVEN MORE
smooth = surf.smooth(n_iter=1000)
smooth.plot(show_edges=True, cpos=cpos)
../../_images/sphx_glr_volume-smoothing_004.png

Total running time of the script: ( 0 minutes 8.116 seconds)

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