| Name | CTLearn JSON |
| Version |
0.10.2
JSON |
| download |
| home_page | None |
| Summary | 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). |
| upload_time | 2025-03-21 17:11:28 |
| maintainer | None |
| docs_url | None |
| author | Ari Brill, Bryan Kim, Tjark Miener |
| requires_python | >=3.10 |
| license | BSD-3-Clause |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
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>`_
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"description": "\nCTLearn: Deep Learning for IACT Event Reconstruction\n====================================================\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3342952.svg\n :target: https://doi.org/10.5281/zenodo.3342952\n :alt: DOI\n\n.. image:: https://img.shields.io/pypi/v/ctlearn\n :target: https://pypi.org/project/ctlearn/\n :alt: Latest Release\n\n.. image:: https://github.com/ctlearn-project/ctlearn/actions/workflows/python-package-conda.yml/badge.svg\n :target: https://github.com/ctlearn-project/ctlearn/actions/workflows/python-package-conda.yml\n :alt: Continuos Integration\n \n.. image:: images/CTLearnTextCTinBox_WhiteBkgd.png\n :target: images/CTLearnTextCTinBox_WhiteBkgd.png\n :alt: CTLearn Logo\n\n\nCTLearn 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>`_.\n\n* Code, feature requests, bug reports, pull requests: https://github.com/ctlearn-project/ctlearn\n* Documentation: https://ctlearn.readthedocs.io\n* License: BSD-3\n\nInstallation for users\n----------------------\n\nDownload and install `Anaconda <https://www.anaconda.com/download/>`_\\ , or, for a minimal installation, `Miniconda <https://conda.io/miniconda.html>`_.\n\nThe following command will set up a conda virtual environment, add the\nnecessary package channels, and install CTLearn specified version and its dependencies:\n\n.. code-block:: bash\n\n CTLEARN_VER=0.10.2\n wget https://raw.githubusercontent.com/ctlearn-project/ctlearn/v$CTLEARN_VER/environment.yml\n conda env create -n [ENVIRONMENT_NAME] -f environment.yml\n conda activate [ENVIRONMENT_NAME]\n pip install ctlearn==$CTLEARN_VER\n ctlearn -h\n\n\nThis 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).\n\nSee 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.\n\nCiting this software\n--------------------\n\nPlease 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.\n\nTeam\n----\n\n.. list-table::\n :header-rows: 1\n\n * - .. image:: https://github.com/aribrill.png?size=100\n :target: https://github.com/aribrill\n :alt: Ari Brill\n \n - .. image:: https://github.com/bryankim96.png?size=100\n :target: https://github.com/bryankim96\n :alt: Bryan Kim\n \n - .. image:: https://github.com/TjarkMiener.png?size=100\n :target: https://github.com/TjarkMiener\n :alt: Tjark Miener\n \n - .. image:: https://github.com/nietootein.png?size=100\n :target: https://github.com/nietootein\n :alt: Daniel Nieto\n \n * - `Ari Brill <https://github.com/aribrill>`_\n - `Bryan Kim <https://github.com/bryankim96>`_\n - `Tjark Miener <https://github.com/TjarkMiener>`_\n - `Daniel Nieto <https://github.com/nietootein>`_\n\n\nCollaborators\n-------------\n\n.. list-table::\n :header-rows: 1\n\n * - .. image:: https://github.com/qi-feng.png?size=100\n :target: https://github.com/qi-feng\n :alt: Qi Feng\n\n - .. image:: https://github.com/rlopezcoto.png?size=100\n :target: https://github.com/rlopezcoto\n :alt: Ruben Lopez-Coto\n\n * - `Qi Feng <https://github.com/qi-feng>`_\n - `Ruben Lopez-Coto <https://github.com/rlopezcoto>`_\n\n\nAlumni\n------\n\n.. list-table::\n :header-rows: 1\n\n * - .. image:: https://github.com/Jsevillamol.png?size=100\n :target: https://github.com/Jsevillamol\n :alt: Jaime Sevilla\n \n - .. image:: https://github.com/hrueda25.png?size=100\n :target: https://github.com/hrueda25\n :alt: H\u00e9ctor Rueda\n \n - .. image:: https://github.com/jredondopizarro.png?size=100\n :target: https://github.com/jredondopizarro\n :alt: Juan Redondo Pizarro\n \n - .. image:: https://github.com/LucaRomanato.png?size=100\n :target: https://github.com/LucaRomanato\n :alt: LucaRomanato\n \n - .. image:: https://github.com/sahilyadav27.png?size=100\n :target: https://github.com/sahilyadav27\n :alt: Sahil Yadav\n \n - .. image:: https://github.com/sgh14.png?size=100\n :target: https://github.com/sgh14\n :alt: Sergio Garc\u00eda Heredia\n \n * - `Jaime Sevilla <https://github.com/Jsevillamol>`_\n - `H\u00e9ctor Rueda <https://github.com/hrueda25>`_\n - `Juan Redondo Pizarro <https://github.com/jredondopizarro>`_\n - `Luca Romanato <https://github.com/LucaRomanato>`_\n - `Sahil Yadav <https://github.com/sahilyadav27>`_\n - `Sergio Garc\u00eda Heredia <https://github.com/sgh14>`_\n",
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