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"""
.. _create_poly:
Create PolyData
~~~~~~~~~~~~~~~
Creating a :class:`pyvista.PolyData` (surface mesh) from vertices and faces.
"""
from __future__ import annotations
import numpy as np
import pyvista as pv
# %%
# A PolyData object can be created quickly from numpy arrays. The vertex array
# contains the locations of the points in the mesh and the face array contains
# the number of points of each face and the indices of the vertices which
# comprise that face.
# mesh points
vertices = np.array([[0, 0, 0], [1, 0, 0], [1, 1, 0], [0, 1, 0], [0.5, 0.5, -1]])
# mesh faces
faces = np.hstack(
[
[4, 0, 1, 2, 3], # square
[3, 0, 1, 4], # triangle
[3, 1, 2, 4], # triangle
],
)
surf = pv.PolyData(vertices, faces)
# plot each face with a different color
surf.plot(
scalars=np.arange(3),
cpos=[-1, 1, 0.5],
show_scalar_bar=False,
show_edges=True,
line_width=5,
)
# %%
# Polygonal PolyData
# ~~~~~~~~~~~~~~~~~~
# Create a three face polygonal mesh directly from points and faces.
#
# .. note::
# It is generally more efficient to use a numpy array rather than stacking
# lists for large meshes.
points = np.array(
[
[0.0480, 0.0349, 0.9982],
[0.0305, 0.0411, 0.9987],
[0.0207, 0.0329, 0.9992],
[0.0218, 0.0158, 0.9996],
[0.0377, 0.0095, 0.9992],
[0.0485, 0.0163, 0.9987],
[0.0572, 0.0603, 0.9965],
[0.0390, 0.0666, 0.9970],
[0.0289, 0.0576, 0.9979],
[0.0582, 0.0423, 0.9974],
[0.0661, 0.0859, 0.9941],
[0.0476, 0.0922, 0.9946],
[0.0372, 0.0827, 0.9959],
[0.0674, 0.0683, 0.9954],
],
)
face_a = [6, 0, 1, 2, 3, 4, 5]
face_b = [6, 6, 7, 8, 1, 0, 9]
face_c = [6, 10, 11, 12, 7, 6, 13]
faces = np.concatenate((face_a, face_b, face_c))
mesh = pv.PolyData(points, faces)
mesh.plot(show_edges=True, line_width=5)
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