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"author": "Thomas Vuillaume, Mikael Jacquemont",
"author_email": "thomas.vuillaume@lapp.in2p3.fr",
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"description": "=======\nctaplot\n=======\n\nctaplot is a collection of functions to make instrument response functions (IRF) and reconstruction quality-checks plots for Imaging Atmospheric Cherenkov Telescopes such as CTA\n\nGiven a list of reconstructed and simulated quantities, compute and plot the Instrument Response Functions such as:\n\n* angular resolution\n* energy resolution\n* effective surface\n* impact point resolution\n\n\nYou may find examples in the `documentation `_.\n\n\n----\n\n\n* Code : https://github.com/vuillaut/ctaplot\n* Documentation : https://ctaplot.readthedocs.io/en/latest/\n* Author contact: Thomas Vuillaume - thomas.vuillaume@lapp.in2p3.fr\n* License: MIT\n\n----\n\nThe CTA instrument response functions data used in ctaplot come from the CTA Consortium and Observatory and may be found on the `cta-observatory website `_ .\n\nIn cases for which the CTA instrument response functions are used in a research project, we ask to add the following acknowledgement in any resulting publication: \n\n\u201cThis research has made use of the CTA instrument response functions provided by the CTA Consortium and Observatory, see http://www.cta-observatory.org/science/cta-performance/ (version prod3b-v2) for more details.\u201d\n\n----\n\n\n.. image:: https://readthedocs.org/projects/ctaplot/badge/?version=latest\n :target: https://ctaplot.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n \n.. image:: https://travis-ci.org/vuillaut/ctaplot.svg?branch=master\n :target: https://travis-ci.org/vuillaut/ctaplot\n \n.. image:: https://img.shields.io/badge/license-MIT-blue.svg\n :target: https://opensource.org/licenses/MIT\n :alt: License: MIT\n\n\nInstall\n=======\n\n\nRequirements packages:\n\n* python > 3.6\n* numpy \n* scipy>=0.19 \n* matplotlib>=2.0\n* astropy\n\nWe recommend the use of `anaconda `_\n\nThe package is available through pip:\n\n.. code-block:: bash\n\n pip install ctaplot\n\n\n.. code-block:: bash\n\n export GAMMABOARD_DATA=path_to_the_data_directory\n\n\nWe recommend that you add this line to your bash source file (`$HOME/.bashrc` or `$HOME/.bash_profile`)\n\n\n\nGammaBoard\n==========\n\n*A dashboard to show them all.*\n\n\nGammaBoard is a simple jupyter dashboard thought to display metrics assessing the reconstructions performances of\nImaging Atmospheric Cherenkov Telescopes (IACTs).\nDeep learning is a lot about bookkeeping and trials and errors. GammaBoard ease this bookkeeping and allows quick\ncomparison of the reconstruction performances of your machine learning experiments.\n\nIt is a working prototype used in CTA, especially by the [GammaLearn](https://gitlab.lapp.in2p3.fr/GammaLearn/) project.\n\n\nRun GammaBoard\n--------------\n\nTo launch the dashboard, you can simply try the command:\n\n.. code-block:: bash\n\n gammaboard\n\nThis will run a temporary copy of the dashboard (a jupyter notebook).\nLocal changes that you make in the dashboard will be discarded afterwards.\n\nGammaBoard is using data in a specific directory storing all your experiments files.\nThis directory is known under `$GAMMABOARD_DATA` by default.\nHowever, you can change the path access at any time in the dashboard itself.\n\nDemo\n----\n\nHere is a simple demo of GammaBoard: \n\n* On top the plots (metrics) such as angular resolution and energy resolution.\n* Below, the list of experiments in the user folder.\n\nWhen an experiment is selected in the list, the data is automatically loaded, the metrics computed and displayed.\nA list of information provided during the training phase is also displayed.\nAs many experiments results can be overlaid.\nWhen an experiment is deselected, it simply is removed from the plots.\n\n\n.. image:: share/gammaboard.gif\n :alt: gammaboard_demo",
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