Create PolyData

Creating a pyvista.PolyData (surface mesh) from vertices and faces.

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)