Welcome to perch's documentation!
===================================

**perch** is a Python package for applying the topological technique of persistent homology to astronomical images & data cubes.

Persistent homology identifies and characterizes multi-scale structures in your data by tracking topological features (peaks, rings, voids) across all threshold values.

Check out the :doc:`usage` section for :ref:`installation` instructions, skim the :doc:`concepts` overview for the theory, then move on to the :doc:`quickstart` guide to start analyzing your data.

.. note::

   This project is under active development.

Contents
--------

.. toctree::
   :maxdepth: 2

   usage
   concepts
   quickstart
   advanced
   api
   acknowledgements

Getting Started
---------------

New to perch? Start here:

1. :doc:`usage` - Install perch and its dependencies
2. :doc:`concepts` - Understand the theory behind persistent homology
3. :doc:`quickstart` - Your first 2D analysis
4. :doc:`advanced` - 3D data, FITS files, and advanced techniques
5. :doc:`api` - Detailed API reference

Indices and tables
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* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`