Steenroder/steenroder
Computation of persistence Steenrod barcodes
This package helps researchers in applied topology enhance their analysis of filtered cellular complexes. It takes topological data and computes advanced Sq k-barcodes, which offer a more powerful and discriminatory representation than traditional barcodes. This is ideal for mathematicians and data scientists working with complex datasets where subtle topological features are crucial.
No commits in the last 6 months. Available on PyPI.
Use this if you need to extract more detailed and discriminative topological features from your data beyond what standard persistence barcodes can provide.
Not ideal if you are looking for a general-purpose topological data analysis tool or are unfamiliar with cohomology operations and persistence Steenrod modules.
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Language
Jupyter Notebook
License
MIT
Category
Last pushed
May 30, 2022
Commits (30d)
0
Dependencies
5
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