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yemeen merged 2 commits into from
Apr 24, 2026
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add joss badge #105

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add joss badge
yemeen Apr 24, 2026
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Update citing and add JOSS publication link/image
yemeen Apr 24, 2026
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5 changes: 4 additions & 1 deletion README.md
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# `ect`: A python package for computing the Euler Characteristic Transform
# `ect`: A python package for the Euler Characteristic Transform

[![DOI](https://joss.theoj.org/papers/10.21105/joss.09691/status.svg)](https://doi.org/10.21105/joss.09691)


Python computation tools for computing the Euler Characteristic Transform of embedded complexes.

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9 changes: 6 additions & 3 deletions doc_source/citing.rst
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Citing
=======
======

To cite `ect` please use the following publication:
To cite the ``ect`` software, please use the following `JOSS <https://joss.theoj.org/>`_ publication:

Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. `doi:10.1080/00029890.2024.2409616 <https://doi.org/10.1080/00029890.2024.2409616>`_. 2024.
Ayub, Yemeen, Elizabeth Munch, Sarah McGuire Scullen, and Daniel H. Chitwood. ect: A Python Package for the Euler Characteristic Transform. Journal of Open Source Software, 11(120), 9691. `doi:10.21105/joss.09691 <https://doi.org/10.21105/joss.09691>`_. 2026.

For background on the Euler Characteristic Transform itself, see:

Munch, Elizabeth. An Invitation to the Euler Characteristic Transform. The American Mathematical Monthly, 132(1), 15-25. `doi:10.1080/00029890.2024.2409616 <https://doi.org/10.1080/00029890.2024.2409616>`_. 2024.
4 changes: 4 additions & 0 deletions doc_source/index.rst
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ect: Euler Characteristic Transform in Python
=============================================

.. image:: https://joss.theoj.org/papers/10.21105/joss.09691/status.svg
:target: https://doi.org/10.21105/joss.09691
:alt: Published in the Journal of Open Source Software

The `ect` package is a library of tools for computing the Euler Characteristic Transform of embedded cell complexes with arbitrary dimensional cells. This package is to aid researchers and practitioners in topological data analysis and related fields (such as computational geometry, network science, and biological shape analysis) who require scalable, Python-native tools for extracting and using topological features from embedded complexes.

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