A Python library for performing numerical differential geometry on smooth closed surfaces based on Global Polynomial Level Sets (GPLS). 1
Starting with a pointset representation of a surface, GPLS can be used to approximate a broad class of smooth surfaces as affine algebraic varieties. With this polynomial representation, differential-geometric quantities like mean and Gauss curvature can be efficiently and accurately computed. This compressed representation significantly reduces the computational cost of 3d surface simulations.
Since this implementation is a prototype, we currently only provide the installation by self-building from source. We recommend to using git to get the minterpy-levelsets source:
git clone https://codebase.helmholtz.cloud/interpol/minterpy-levelsets.gitSwitch to the conda or venv virtual environment of your choice where you would like to install the library.
From within the environment, install using [pip],
pip install [-e] .where the flag -e means the package is directly linked
into the python site-packages of your Python version.
You must not use the command python setup.py install to install minterpy,
as you cannot always assume the files setup.py will always be present
in the further development of minterpy.
Documentation is a WIP. Please refer to the example Jupyter notebooks in the examples/ directory to get started with the library.
- Sachin Krishnan Thekke Veettil (MPI CBG/TU Dresden) sthekke@mpi-cbg.de
- Gentian Zavalani (HZDR/CASUS) g.zavalani@hzdr.de
- Michael Hecht (HZDR/CASUS) m.hecht@hzdr.de
- Uwe Hernandez Acosta (HZDR/CASUS)
- Damar Wicaksono (HZDR/CASUS)
- Minterpy development team
Open an issue or submit PRs.
Footnotes
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[Veettil, Sachin K. Thekke, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, and Michael Hecht. "Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces." arXiv preprint arXiv:2212.11536 (2022)] (https://arxiv.org/abs/2212.11536). ↩