PyTessel
Purpose
PyTessel is a Python package for constructing isosurfaces from 3D scalar fields using the marching cubes algorithm. It is designed for scientific visualization, computational geometry, and mesh generation workflows. While PyTessel was originally developed for rendering molecular orbitals, it is flexible enough to tessellate arbitrary scalar fields.
Installation
pip install pytessel
Getting started
The example below constructs an isosurface of a three-dimensional Gaussian function.
The resulting surface is written to test.ply, which can be viewed using tools
such as:
ctmviewer(Linux)3D Viewer(Windows, free via Microsoft Store)- Blender, MeshLab, etc.
from pytessel import PyTessel
import numpy as np
def main():
pytessel = PyTessel()
# Generate a regular grid
x = np.linspace(0, 10, 50)
# Grid ordering:
# z is the slowest-moving index, x is the fastest-moving index
grid = np.flipud(
np.vstack(np.meshgrid(x, x, x, indexing='ij')).reshape(3, -1)
).T
R = [5, 5, 5]
scalarfield = np.reshape(
np.array([gaussian(r, R) for r in grid]),
(len(x), len(x), len(x))
)
unitcell = np.diag(np.ones(3) * 10.0)
vertices, normals, indices = pytessel.marching_cubes(
scalarfield.flatten(),
scalarfield.shape,
unitcell.flatten(),
0.1
)
pytessel.write_ply('test.ply', vertices, normals, indices)
def gaussian(r, R):
return np.exp(-(r - R).dot(r - R))
if __name__ == '__main__':
main()
Isosurface quality
The script below demonstrates how grid resolution affects surface quality. Six isosurfaces of an icosahedral metaball are generated using grids of:
10×10×1020×20×2025×25×2550×50×50100×100×100200×200×200
Each surface is exported as a .ply file and rendered using Blender.
from pytessel import PyTessel
import numpy as np
def main():
"""
Build 6 .ply files of increasing quality
"""
pytessel = PyTessel()
for nrpoints in [10, 20, 25, 50, 100, 200]:
sz = 3
x = np.linspace(-sz, sz, nrpoints)
y = np.linspace(-sz, sz, nrpoints)
z = np.linspace(-sz, sz, nrpoints)
xx, yy, zz, field = icosahedron_field(x, y, z)
unitcell = np.diag(np.ones(3) * sz * 2)
isovalue = 3.75
vertices, normals, indices = pytessel.marching_cubes(
field.flatten(),
field.shape,
unitcell.flatten(),
isovalue
)
pytessel.write_ply(
f'icosahedron_{nrpoints:03d}.ply',
vertices,
normals,
indices
)
def icosahedron_field(x, y, z):
"""
Produce a scalar field for icosahedral metaballs
"""
phi = (1 + np.sqrt(5)) / 2
vertices = [
[0, 1, phi], [0, -1, -phi], [0, 1, -phi], [0, -1, phi],
[1, phi, 0], [-1, -phi, 0], [1, -phi, 0], [-1, phi, 0],
[phi, 0, 1], [-phi, 0, -1], [phi, 0, -1], [-phi, 0, 1]
]
xx, yy, zz = np.meshgrid(x, y, z)
field = np.zeros_like(xx)
for v in vertices:
field += metaball(xx, yy, zz, v[0], v[1], v[2])
return xx, yy, zz, field
def metaball(x, y, z, X0, Y0, Z0):
"""
Single metaball function
"""
return 1 / ((x - X0)**2 + (y - Y0)**2 + (z - Z0)**2)
if __name__ == '__main__':
main()
Gallery
Stanford Bunny
Gyroid surface
1 maintainer
Metadata
1 maintainer
Release files for pytessel 1.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pytessel-1.3.0.tar.gz | 5.0 MB | Details |
Built distributions (wheels)
Total release size: 21.9 MB
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