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pytetwild is a Python library for mesh tetrahedralization. It is a Python wrapper around the efficient C++ library for tetrahedral meshing provided by fTetWild.

Installation

We have pre-built wheels for Python 3.10 - Python 3.14 for Windows, Linux, and macOS.

The recommended way to install pytetwild is via PyPI:

pip install pytetwild[all]

This installs pyvista by default, which you can use to tetrahedralize sufrace meshes from PyVista. Alternatively you can just install with pip install pytetwild for a lighter install.

You can also clone the repository and install it from source, but since there’s C++ involved, the build is a bit more complicated. See CONTRIBUTING.md for more details.

Usage

To tetrahedralize a surface mesh from PyVista, you’ll need to first install pyvista as it’s not a dependency and then run:

import pyvista as pv
import pytetwild

# Load or create a PyVista PolyData surface mesh
# Here, we'll create a simple sphere mesh as an example
surface_mesh = pv.Icosphere(nsub=2)

# Convert the surface mesh to a tetrahedral mesh. For this example let's
# use a coarse mesh
tetrahedral_mesh = pytetwild.tetrahedralize_pv(surface_mesh, edge_length_fac=1)

# Visualize the tetrahedral mesh in an "exploded" view
tetrahedral_mesh.explode(0.5).plot(
    show_edges=True, zoom=1.6, ssao=True, anti_aliasing="ssaa"
)
https://github.com/pyvista/pytetwild/raw/main/exploded-sphere.png

You can also work with raw arrays. Here’s a simple cube that we turn into tetrahedra.

import numpy as np
import pytetwild

# Define vertices of the cube
vertices = np.array([
    [0, 0, 0],  # Vertex 0
    [1, 0, 0],  # Vertex 1
    [1, 1, 0],  # Vertex 2
    [0, 1, 0],  # Vertex 3
    [0, 0, 1],  # Vertex 4
    [1, 0, 1],  # Vertex 5
    [1, 1, 1],  # Vertex 6
    [0, 1, 1]   # Vertex 7
])

# Define faces using vertex indices
# Each face is a rectangle (also accepts triangles)
faces = np.array([
    [0, 1, 2, 3],  # Front face
    [1, 5, 6, 2],  # Right face
    [5, 4, 7, 6],  # Back face
    [4, 0, 3, 7],  # Left face
    [4, 5, 1, 0],  # Bottom face
    [3, 2, 6, 7]   # Top face
])
v_out, tetra = pytetwild.tetrahedralize(vertices, faces, optimize=False)

Usage - Sizing Field

To vary cell size across the mesh rather than using one edge length everywhere, pass a background tetrahedral mesh carrying the target edge length at each of its points. This is fTetWild’s --bg-mesh.

import numpy as np
import pyvista as pv
import pytetwild

# Background mesh covering the input, refined on one side
background = pv.ImageData(
    dimensions=(5, 5, 5), spacing=(0.3, 0.3, 0.3), origin=(-0.6, -0.6, -0.6)
).to_tetrahedra()
background.point_data["target"] = np.where(
    background.points[:, 0] < 0, 0.04, 0.2
)

mesh = pytetwild.tetrahedralize_pv(
    pv.Sphere(), sizing_field=background, sizing_field_scalars="target"
)

The value at any point is interpolated over the background tetrahedron containing it, and anywhere the background mesh does not cover falls back to the global ideal edge length. Note this is unrelated to disable_filtering, which keeps the internal background mesh fTetWild builds for itself.

Usage - Options

We’ve surfaced a several parameters to each of our interfaces tetrahedralize and tetrahedralize_pv:

Parameters
----------
edge_length_fac : float, default: 0.05
    Tetrahedral edge length as a function of bounding box diagonal. The
    default ideal edge length is ``bb/20`` (bounding box divided by
    20). Ignored when ``edge_length_abs`` is input.
edge_length_abs : float, optional
    Absolute ideal edge length. When input ``edge_length_fac`` is ignored.
optimize : bool, default: True
    Improve the minimum scaled Jacobean for each cell. This leads to higher
    cell quality at the expense of computation time. Optimization level is
    dependent on ``stop_energy`` and ``num_opt_iter``.
simplify : bool, default: True
    Simplfiy the input mesh surface before tetrahedralization.
epsilon : float, default 1e-3
    Envelop size, specifying the maximum distance of the output surface
    from the input surface, relative to the bounding box size.
stop_energy : float, default: 10.0
    The mesh optimization stops when the conformal AMIPS energy reaches
    ``stop_energy``.
coarsen : bool, default: False
    Coarsen the output as much as possible, while maintaining the mesh
    quality.
num_threads : int, default: 0
    Set number of threads used. 0 (default) uses all available cores.
num_opt_iter : int, default: 80
    Maximum number of optimization iterations if ``optimize=True``.
loglevel : int, default: 6
    Set log level (0 = most verbose, 6 = minimal output).
quiet : bool, default: False
    Disable all output. Overrides ``loglevel``.
sizing_field : pv.UnstructuredGrid, optional
    ``tetrahedralize_pv`` only. All-tetrahedral mesh supplying a
    spatially varying target edge length. Requires ``optimize=True``.
sizing_field_scalars : str, optional
    ``tetrahedralize_pv`` only. Name of the point array on
    ``sizing_field`` holding the target edge length. Defaults to its
    active point scalars.
bg_vertices, bg_tets, bg_values : np.ndarray, optional
    ``tetrahedralize`` only. The same sizing field as raw arrays:
    points ``(n, 3)``, tetrahedra ``(m, 4)``, and the target edge
    length at each point ``(n,)``.

License and Acknowledgments

This project relies on fTetWild and credit goes to the original authors for their efficient C++ library for tetrahedral meshing. That work is licensed under the Mozilla Public License v2.0.

The work in this repository is also licensed under the Mozilla Public License v2.0.

Support

If you are having issues, please feel free to raise an Issue.

Key dates

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Latest release

Owner

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1 maintainer

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Avatar for pyvista from gravatar.com pyvista

Credits

Author: Alex Kaszynski

License

Mozilla Public License 2.0 (MPL 2.0)

Requires

Python <3.15, >=3.10

Provides Extra

all tests dev

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