CTLearn 0.10.2
CTLearn is a package under active development to run deep learning models to analyze data from all major current and future arrays of imaging atmospheric Cherenkov telescopes (IACTs).
License: BSD-3-Clause
Requires Python: >=3.10


CTLearn: Deep Learning for IACT Event Reconstruction
====================================================

.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3342952.svg
   :target: https://doi.org/10.5281/zenodo.3342952
   :alt: DOI

.. image:: https://img.shields.io/pypi/v/ctlearn
    :target: https://pypi.org/project/ctlearn/
    :alt: Latest Release

.. image:: https://github.com/ctlearn-project/ctlearn/actions/workflows/python-package-conda.yml/badge.svg
    :target: https://github.com/ctlearn-project/ctlearn/actions/workflows/python-package-conda.yml
    :alt: Continuos Integration
    
.. image:: images/CTLearnTextCTinBox_WhiteBkgd.png
   :target: images/CTLearnTextCTinBox_WhiteBkgd.png
   :alt: CTLearn Logo


CTLearn is a package under active development to run deep learning models to analyze data from all major current and future arrays of imaging atmospheric Cherenkov telescopes (IACTs). CTLearn can load R1/DL0/DL1 data from `CTAO <https://www.cta-observatory.org/>`_ (Cherenkov Telescope Array Observatory), `FACT <https://www.isdc.unige.ch/fact/>`_\ , `H.E.S.S. <https://www.mpi-hd.mpg.de/hfm/HESS/>`_\ , `LST-1 <https://www.lst1.iac.es/>`_\ , `MAGIC <https://magic.mpp.mpg.de/>`_\ , and `VERITAS <https://veritas.sao.arizona.edu/>`_ telescopes reduced by `ctapipe <https://github.com/cta-observatory/ctapipe>`_ and processed by `DL1DataHandler <https://github.com/cta-observatory/dl1-data-handler>`_.

* Code, feature requests, bug reports, pull requests: https://github.com/ctlearn-project/ctlearn
* Documentation: https://ctlearn.readthedocs.io
* License: BSD-3

Installation for users
----------------------

Download and install `Anaconda <https://www.anaconda.com/download/>`_\ , or, for a minimal installation, `Miniconda <https://conda.io/miniconda.html>`_.

The following command will set up a conda virtual environment, add the
necessary package channels, and install CTLearn specified version and its dependencies:

.. code-block:: bash

   CTLEARN_VER=0.10.2
   wget https://raw.githubusercontent.com/ctlearn-project/ctlearn/v$CTLEARN_VER/environment.yml
   conda env create -n [ENVIRONMENT_NAME] -f environment.yml
   conda activate [ENVIRONMENT_NAME]
   pip install ctlearn==$CTLEARN_VER
   ctlearn -h


This should automatically install all dependencies (NOTE: this may take some time, as by default MKL is included as a dependency of NumPy and it is very large).

See the documentation for further information like `installation instructions for developers <https://ctlearn.readthedocs.io/en/latest/installation.html#installing-with-pip-setuptools-from-source-for-development>`_, `package usage <https://ctlearn.readthedocs.io/en/stable/usage.html>`_, and `dependencies <https://ctlearn.readthedocs.io/en/stable/installation.html#dependencies>`_ among other topics.

Citing this software
--------------------

Please cite the corresponding version using the `DOIs from Zenodo <https://zenodo.org/search?q=parent.id:3342952&sort=version&f=allversions:true>`_ if this software package is used to produce results for any publication.

Team
----

.. list-table::
   :header-rows: 1

   * - .. image:: https://github.com/aribrill.png?size=100
        :target: https://github.com/aribrill
        :alt: Ari Brill
     
     - .. image:: https://github.com/bryankim96.png?size=100
        :target: https://github.com/bryankim96
        :alt: Bryan Kim
     
     - .. image:: https://github.com/TjarkMiener.png?size=100
        :target: https://github.com/TjarkMiener
        :alt: Tjark Miener
     
     - .. image:: https://github.com/nietootein.png?size=100
        :target: https://github.com/nietootein
        :alt: Daniel Nieto
     
   * - `Ari Brill <https://github.com/aribrill>`_
     - `Bryan Kim <https://github.com/bryankim96>`_
     - `Tjark Miener <https://github.com/TjarkMiener>`_
     - `Daniel Nieto <https://github.com/nietootein>`_


Collaborators
-------------

.. list-table::
   :header-rows: 1

   * - .. image:: https://github.com/qi-feng.png?size=100
        :target: https://github.com/qi-feng
        :alt: Qi Feng

     - .. image:: https://github.com/rlopezcoto.png?size=100
        :target: https://github.com/rlopezcoto
        :alt: Ruben Lopez-Coto

   * - `Qi Feng <https://github.com/qi-feng>`_
     - `Ruben Lopez-Coto <https://github.com/rlopezcoto>`_


Alumni
------

.. list-table::
   :header-rows: 1

   * - .. image:: https://github.com/Jsevillamol.png?size=100
        :target: https://github.com/Jsevillamol
        :alt: Jaime Sevilla
     
     - .. image:: https://github.com/hrueda25.png?size=100
        :target: https://github.com/hrueda25
        :alt: Héctor Rueda
     
     - .. image:: https://github.com/jredondopizarro.png?size=100
        :target: https://github.com/jredondopizarro
        :alt: Juan Redondo Pizarro
     
     - .. image:: https://github.com/LucaRomanato.png?size=100
        :target: https://github.com/LucaRomanato
        :alt: LucaRomanato
     
     - .. image:: https://github.com/sahilyadav27.png?size=100
        :target: https://github.com/sahilyadav27
        :alt: Sahil Yadav
     
     - .. image:: https://github.com/sgh14.png?size=100
        :target: https://github.com/sgh14
        :alt: Sergio García Heredia
     
   * - `Jaime Sevilla <https://github.com/Jsevillamol>`_
     - `Héctor Rueda <https://github.com/hrueda25>`_
     - `Juan Redondo Pizarro <https://github.com/jredondopizarro>`_
     - `Luca Romanato <https://github.com/LucaRomanato>`_
     - `Sahil Yadav <https://github.com/sahilyadav27>`_
     - `Sergio García Heredia <https://github.com/sgh14>`_