petls 1.0.0

PErsistent Topological Laplacian Software: a Python Library to Compute Persistent Topological Laplacians

See the documentation for details on requirements, installation, and API usage.

Python Dependencies

• Eigen version 3.4 or higher
• pybind11
• scipy
• numpy
• Boost

Python installation and usage

The simplest way to install is:

pip install petls

The next simplest is to clone the repository and run

pip install .

After that, you're all set:

   $ python
   >>> from petls import Rips
   >>> import numpy as np
   >>> points = np.array([[0, 0], [0, 3], [4, 0], [4, 3]])
   >>> complex = Rips(points, max_dim=3)
   >>> complex.spectra(dim=1, a=3, b=4)
   [2.0, 2.0]

C++ installation

First, make and enter the cpp/build directory.

   cd cpp
   mkdir build
   cd build

Next, we make and install the project. If you have root access:

   cmake ..
   sudo make all install

If you do not have root access (e.g. on an HPC):

   cmake -DCMAKE_INSTALL_PREFIX=<location> ..
   make all install

Usually CMAKE_INSTALL_PREFIX is something like ~/custom_libraries/.

For examples of how to include the library, see the examples directory, e.g. examples/basic_cpp/.

Acknowledgements

This work was supported in part by NIH grant R35GM148196, NSF grant DMS-2052983, and MSU Research Foundation.

Citation

If you wish to cite this work, please use the following citation:

@misc{jones2025petlspersistenttopologicallaplacian,
      title={PETLS: PErsistent Topological Laplacian Software}, 
      author={Benjamin Jones and Guo-Wei Wei},
      year={2025},
      eprint={2508.11560},
      archivePrefix={arXiv},
      primaryClass={math.AT},
      url={https://arxiv.org/abs/2508.11560}, 
}