pyect 0.1.7

Generalized computation of the weighted Euler characteristic transform using PyTorch.

pyECT

The Weighted Euler Characteristic Transform (WECT) is a mathematical tool used to analyze and summarize geometric and topological features of data. This package provides an efficient and simple implementation of the WECT using PyTorch.

This codebase accompanies this preprint. If you use this package, please include the following citation in your work:

@misc{cisewskikehe2025vectorizedcomputationeulercharacteristic,
      title={Vectorized Computation of Euler Characteristic Functions and Transforms}, 
      author={Jessi Cisewski-Kehe and Brittany Terese Fasy and Alexander McCleary and Eli Quist and Jack Ruder},
      year={2025},
      eprint={2511.03909},
      archivePrefix={arXiv},
      primaryClass={cs.CG},
      url={https://arxiv.org/abs/2511.03909}, 
}

Installation

To install pyECT, use pip:

pip install pyect 

Usage

Here's a simple example of how to use pyECT:

from pyect import WECT

# Example data and weight function
data = [...]  # Replace with your data
weight_function = lambda x: x**2  # Replace with your weight function

# Compute the WECT
wect = WECT(data, weight_function)
result = wect.compute()

print("WECT result:", result)

For more detailed examples, please see the /examples directory.

Contributing

Contributions are welcome! If you'd like to contribute, please fork the repository and submit a pull request. For major changes, please open an issue first to discuss what you'd like to change.

License

This project is licensed under the MIT License. See the LICENSE file for details.