Awesome
A Python Geometry Processing Toolbox
Authors: Silvia Sellán, University of Toronto and Oded Stein, University of Southern California
This is a very young library of general geometry processing Python research utility functions that evolves from our personal student codebases.
Installation
Latest stable release (recommended)
You should be able install the latest release of Gpytoolbox with pip:
python -m pip install gpytoolbox
A conda installation will be supported in the future.
From Git
If you want to build Gpytoolbox from a specific git commit; for example, because
you want to develop for Gpytoolbox or because you want some functionality that
is in the main
branch but hasn't been pushed to any release yet, you should be
able to do so by cloning Gpytoolbox's github
repo and running
python -m pip install numpy
python -m pip install .
Documentation
You can find documentation for all our functions in our
website. You can also view the documentation for a
specific function by running help(function_name)
or function_name.__doc__
;
for example,
>>> from gpytoolbox import grad
>>> help(grad)
Finite element gradient matrix
Given a triangle mesh or a polyline, computes the finite element gradient matrix assuming piecewise linear hat function basis.
Parameters
----------
V : numpy double array
Matrix of vertex coordinates
F : numpy int array, optional (default None)
Matrix of triangle indices
Returns
-------
G : scipy sparse.csr_matrix
Sparse FEM gradient matrix
See Also
--------
cotangent_laplacian.
Notes
-----
Examples
--------
TO-DO
Contribute
We hope you find our current version of our library useful. At the same time, we encourage you to ask not what Gpytoolbox can do for you, but what you can do for Gpytoolbox.
Since Gpytoolbox is a very young library, we want to make it as easy as possible
for others to contribute to it and help it grow. You can contribute by adding a
new function in a new file inside src/gpytoolbox/
, or by adding to existing
functions, and submitting a Pull
Request.
We also want to make the contribution process as unintimidating as possible. We will gladly review and edit your code to make sure it acommodates to our standards and we have set up many tests that will let us know if your contribution accidentally breaks anything. If there's any functionality that is not already in this library, is remotely related to geometry processing, and you have used or used in any of your past projects, we encourage you to submit it as-is in a Pull Request. We will gladly credit you in the individual function as well as on this home page.
Note that the code that you contribute will be licensed under the MIT license. Everybody will be able to use this code as long as they credit gpytoolbox (and not you individually).
License
Gpytoolbox's is released under an MIT license (see details),
except for files in the gpytoolbox.copyleft
module, which are under a GPL one
(see details). Functions in the copyleft module must be imported
explicitly; this way, if you import only the main Gpytoolbox module
import gpytoolbox
or individual functions from it,
from gpytoolbox import regular_square_mesh, regular_cube_mesh
you are only bound by the terms of the permissive MIT license. However, if you
import any functionality from gpytoolbox.copyleft
; e.g.,
from gpytoolbox.copyleft import mesh_boolean
you will be bound by the more restrictive GPL license.
Attribution
If you use our library in your research paper, please cite us! You can use the bibtex block below:
@misc{gpytoolbox,
title = {{gptyoolbox}: A Python Geometry Processing Toolbox},
author = {Silvia Sell\'{a}n and Oded Stein and others},
note = {https://gpytoolbox.org/},
year = {2023}
}
Acknowledgements
Several people have, knowingly or unknowingly, greatly contributed to this library. We are thankful to them:
-
Alec Jacobson is the author of the original Matlab gptoolbox on which we inspired ourselves to create this library. Several of our functions are line-by-line translations of his Matlab ones. Thanks, Alec!
-
Nicholas Sharp, the author of the game-changing geometry visualization library polyscope, was extremely helpful in guiding us through setting up and distributing a Python package. Thanks, Nick!
Contributors
- We would like to thank Michael Jäger for being Gpytoolbox's first external contributor (PR #45, PR #69).
- Towaki Takikawa (PR #49)
- Otman Benchekroun (PR #59)
- Abhishek Madan (PR #103)
- Lukas Hermann (PR #135)
- Haoyang Wu (PR #142)
- Dylan Rowe (PR #144)
Basic Optimistic Roadmap
Here are some things we think would be nice to incorporate to future versions of gpytoolbox. If there's one you are missing, feel free to submit a PR adding your item to this bullet list. If you want to contribute to gpytoolbox, a great way to start is by picking any of the items below that does not have an associated PR yet
To-do
- Iterative closest point for mesh alignment
- Basic FEM (cotangent matrix, mass matrix, linear elasticity) for tetrahedral meshes
- ARAP for deformation and parametrization
- Exact geodesic distances
- Heat (approximate) geodesic distance
- Blue noise in random mesh sampling
- Intrinsic triangulation routines
- Fracture mode computation
- Pure-python version of in_element_aabb
- Make all grid sizes, resolutions, etc. into tuples not necessarily numpy arrays
- Add notes on every docstring mentioning libigl implementations
- Tetrahedral mesh implementation of
subdivide.py
- Dihedral angle computation
regular_square_mesh
andregular_cube_mesh
should support different resolutions inx
andy
direction (sensible default when n_y is None, to n_y=n_x)