Computing Surface Normals#

Compute normals on a surface.

import numpy as np

from pyvista import examples

mesh = examples.download_topo_global()
mesh.plot(cmap="gist_earth", show_scalar_bar=False)
c compute normals

Now we have a surface dataset of the globe loaded - unfortunately, the dataset shows the globe with a uniform radius which hides topographic relief. Using pyvista.PolyData.compute_normals(), we can compute the normal vectors on the globe at all points in the dataset, then use the values given in the dataset to warp the surface in the normals direction to create some exaggerated topographic relief.

# Compute the normals in-place and use them to warp the globe
mesh.compute_normals(inplace=True)  # this activates the normals as well
HeaderData Arrays
N Cells2333880
N Points2336041
N Strips0
X Bounds-1.000e+00, 1.000e+00
Y Bounds-1.000e+00, 1.000e+00
Z Bounds-1.000e+00, 1.000e+00
N Arrays3
NameFieldTypeN CompMinMax

Now use those normals to warp the surface

warp = mesh.warp_by_scalar(factor=0.5e-5)

And let’s see it!

warp.plot(cmap="gist_earth", show_scalar_bar=False)
c compute normals

We could also use face or cell normals to extract all the faces of a mesh facing a general direction. In the following snippet, we take a mesh, compute the normals along its cell faces, and extract the faces that face upward.

mesh = examples.download_nefertiti()
# Compute normals
mesh.compute_normals(cell_normals=True, point_normals=False, inplace=True)

# Get list of cell IDs that meet condition
ids = np.arange(mesh.n_cells)[mesh['Normals'][:, 2] > 0.0]

# Extract those cells
top = mesh.extract_cells(ids)

cpos = [
    (-834.3184529757553, -918.4677714398535, 236.5468795300025),
    (11.03829376004883, -13.642289291587957, -35.91218884207208),
    (0.19212361465657216, 0.11401076390090074, 0.9747256344254143),

top.plot(cpos=cpos, color=True)
c compute normals
Open In Colab

Total running time of the script: (0 minutes 43.023 seconds)

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