Skip to main content
PyCon US is happening May 14th-22nd in Pittsburgh, PA USA.  Learn more

tetgen python wrapper for points, PLCs and tetmesh inputs

Project description

tetgenpy

main PyPI version

tetgenpy is a python wrapper for Hang Si's TetGen - A Quality Tetrahedral Mesh Generator and a 3D Delaunay Triangulator. It helps to prepare various types of inputs - points, piecewise linear complexes (PLCs), and tetmesh - for tetrahedron mesh generation based on simple python types, such as list and numpy.ndarray.

Install

pip install tetgenpy

For current development version,

pip install git+https://github.com/tataratat/tetgenpy.git@main

Quick Start

Following is an example for tetrahedralization of a unit cube defined as PLCs. Alternatively, you could also use tetgenpy.PLC class to prepare TetgenIO.

import tetgenpy
import numpy as np

# tetrahedralize unit cube
# define points
points=[
    [0.0, 0.0, 0.0],
    [1.0, 0.0, 0.0],
    [0.0, 1.0, 0.0],
    [1.0, 1.0, 0.0],
    [0.0, 0.0, 1.0],
    [1.0, 0.0, 1.0],
    [0.0, 1.0, 1.0],
    [1.0, 1.0, 1.0],
]

# define facets - it can be list of polygons.
# here, they are hexa faces
facets = [
    [1, 0, 2, 3],
    [0, 1, 5, 4],
    [2, 0, 4, 6],
    [1, 3, 7, 5],
    [3, 2, 6, 7],
    [4, 5, 7, 6],
]

# prepare TetgenIO - input for tetgen
tetgen_in = tetgenpy.TetgenIO()

# set points, facets, and facet_markers.
# facet_markers can be useful for setting boundary conditions
tetgen_in.setup_plc(
    points=points,
    facets=facets,
    facet_markers=[[i] for i in range(1, len(facets) + 1)],
)

# tetgen's tetraheralize function with switches
tetgen_out = tetgenpy.tetrahedralize("qa.05", tetgen_in)

# unpack output
print(tetgen_out.points())
print(tetgen_out.tetrahedra())
print(tetgen_out.trifaces())
print(tetgen_out.trifacemarkers())

This package also provides access to tetgen's binary executable. Try:

$ tetgen -h

Working with vedo

vedo natively supports tetgenpy.TetgenIO types starting with version >=2023.5.1. It is A python module for scientific analysis and visualization of эd objects that can be used to enhance further workflows. You can find an example (same as above) here or simply try:

pip install vedo
vedo -r tetgen1

Contributing

Write an issue or create a pull request! A simple guideline can be found at CONTRIBUTING.md

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page