steenroder 0.1.0
Computation of persistence Steenrod barcodes
License: MIT
Keywords: topological data analysis,persistent homology,persistence steenrod modules,persistence steenrod barcodes

steenroder: A Python package for the computation of persistence Steenrod barcodes
=================================================================================

The widespread use in applied topology of the barcode of filtered
cellular complexes rests on a balance between discriminatory power and
computability. It has long been envision that the strength of this
invariant could be increase using cohomology operations. This package
computes the recently defined *Sq*\ \ *k*\ -barcodes which have been
shown to effectively increase the discriminatory power of barcodes on
real-world data.

For a complete presentation of these invariants please consult
`Persistence Steenrod modules <https://arxiv.org/abs/1812.05031>`__ by
U. Lupo, A. Medina-Mardones and G. Tauzin.

License
-------

``steenroder`` is distributed under the `MIT
license <https://github.com/Steenroder/steenroder/LICENSE>`__.

Documentation
-------------

Please visit https://steenroder.github.io/steenroder/ and navigate to
the version you are interested in.

A number of tutorial notebooks are available in `notebooks/ 
<https://github.com/Steenroder/steenroder/notebooks>`__. Example notebooks
that reproduce the case studies explored in the paper are available in
`notebooks/examples/ 
<https://github.com/Steenroder/steenroder/notebooks/examples>`__.

Installation
------------

Dependencies
~~~~~~~~~~~~

The latest stable version of ``steenroder`` requires:

-  python (>= 3.8)
-  numpy (>= 1.19.1)
-  numba (>= 0.53.0)
-  psutils (>= 5.8.0)
-  gudhi (>= 3.5.0)
-  plotly (>= 5.3.1)

To run the examples, jupyter is required.

.. _installation-1:

Installation
~~~~~~~~~~~~

The simplest way to install ``steenroder`` is using ``pip`` ::

   python -m pip install -U steenroder

If necessary, this will also automatically install all the above
dependencies. Note: we recommend upgrading ``pip`` to a recent version
as the above may fail on very old versions.

Contributing
------------

We welcome new contributors of all experience levels. The Steenroder
community goals are to be helpful, welcoming, and effective. To learn
more about making a contribution to ``steenroder``, please consult the
`relevant
page <https://github.com/Steenroder/steenroder/CONTRIBUTING.md>`__.

Testing
~~~~~~~

After developer installation, you can launch the test suite from outside
the source directory:

::

   pytest steenroder

Important links
---------------

-  Official source code repo: https://github.com/Steenroder/steenroder
-  Download releases: https://pypi.org/project/steenroder/
-  Issue tracker: https://github.com/Steenroder/steenroder/issues

Citing steenroder
-----------------

If you use ``steenroder`` in a scientific publication, we would
appreciate citations to the following paper:

`Persistence Steenrod modules <https://doi.org/10.1007/s41468-022-00093-7>`__

You can use the following BibTeX entry:

::

   @article{steenroder,
      author = {{Lupo}, Umberto and {Medina-Mardones}, Anibal M. and {Tauzin}, Guillaume},
      title = "{Persistence Steenrod modules}",
      journal = {Journal of Applied and Computational Topology},
      year = {2022},
      doi = {10.1007/s41468-022-00093-7},
      URL = {https://doi.org/10.1007/s41468-022-00093-7}
   }

Contacts
--------

steenroder@gmail.com