Metadata-Version: 1.1
Name: ctaplot
Version: 0.5.2
Summary: compute and plot cta IRF
Home-page: https://github.com/cta-observatory/ctaplot
Author: Thomas Vuillaume, Mikael Jacquemont
Author-email: thomas.vuillaume@lapp.in2p3.fr
License: MIT
Description: =======
        ctaplot
        =======
        
        ctaplot is a collection of functions to produce instrument response functions (IRF) and reconstruction quality-checks metrics and plots for Imaging Atmospheric Cherenkov Telescopes such as CTA
        
        Given a list of reconstructed and simulated quantities, compute and plot metric and Instrument Response Functions such as:
        
        * charge resolution
        * ROC curves
        * angular resolution
        * energy resolution
        * effective surface
        * impact point resolution
        
        
        You may find examples in the `documentation <https://ctaplot.readthedocs.io/en/latest/>`_.     
        Or you can run a simple one here:
        
        .. image:: https://mybinder.org/badge_logo.svg
         :target: https://mybinder.org/v2/gh/cta-observatory/ctaplot/master?filepath=examples%2Fnotebooks%2Fresolution_examples.ipynb
        
        ----
        
        
        * Code : https://github.com/cta-observatory/ctaplot
        * Documentation : https://ctaplot.readthedocs.io/en/latest/
        * Author contact: Thomas Vuillaume - thomas.vuillaume@lapp.in2p3.fr
        * License: MIT
        
        ----
        
        The CTA instrument response functions data used in ctaplot come from the CTA Consortium and Observatory and may be found on the `cta-observatory website <http://www.cta-observatory.org/science/cta-performance/>`_ .
        
        In 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:    
        
        “This 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.”
        
        ----
        
        .. image:: https://travis-ci.org/cta-observatory/ctaplot.svg?branch=master
            :target: https://travis-ci.org/cta-observatory/ctaplot
            :alt: Travis CI
        
        .. image:: https://readthedocs.org/projects/ctaplot/badge/?version=latest
           :target: https://ctaplot.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
            
        .. image:: https://img.shields.io/badge/license-MIT-blue.svg
           :target: https://opensource.org/licenses/MIT
           :alt: License: MIT
        
        .. image:: https://mybinder.org/badge_logo.svg
         :target: https://mybinder.org/v2/gh/cta-observatory/ctaplot/master?filepath=examples%2Fnotebooks
        
        
        Install
        =======
        
        
        Requirements packages:
        
        * python > 3.6
        * numpy  
        * scipy>=0.19    
        * matplotlib>=2.0
        * astropy
        
        We recommend the use of `anaconda <https://www.anaconda.com>`_
        
        The package is available through pip:
        
        .. code-block:: bash
        
           pip install ctaplot
        
        
        .. code-block:: bash
        
            export GAMMABOARD_DATA=path_to_the_data_directory
        
        
        We recommend that you add this line to your bash source file (`$HOME/.bashrc` or `$HOME/.bash_profile`)
        
        
        
        GammaBoard
        ==========
        
        *A dashboard to show them all.*
        
        
        GammaBoard is a simple jupyter dashboard thought to display metrics assessing the reconstructions performances of
        Imaging Atmospheric Cherenkov Telescopes (IACTs).
        Deep learning is a lot about bookkeeping and trials and errors. GammaBoard ease this bookkeeping and allows quick
        comparison of the reconstruction performances of your machine learning experiments.
        
        It is a working prototype used in CTA, especially by the [GammaLearn](https://gitlab.lapp.in2p3.fr/GammaLearn/) project.
        
        
        Run GammaBoard
        --------------
        
        To launch the dashboard, you can simply try the command:
        
        .. code-block:: bash
        
            gammaboard
        
        This will run a temporary copy of the dashboard (a jupyter notebook).
        Local changes that you make in the dashboard will be discarded afterwards.
        
        GammaBoard is using data in a specific directory storing all your experiments files.
        This directory is known under `$GAMMABOARD_DATA` by default.
        However, you can change the path access at any time in the dashboard itself.
        
        Demo
        ----
        
        Here is a simple demo of GammaBoard:  
        
        * On top the plots (metrics) such as angular resolution and energy resolution.
        * Below, the list of experiments in the user folder.
        
        When an experiment is selected in the list, the data is automatically loaded, the metrics computed and displayed.
        A list of information provided during the training phase is also displayed.
        As many experiments results can be overlaid.
        When an experiment is deselected, it simply is removed from the plots.
        
        
        .. image:: /share/gammaboard.gif
           :alt: gammaboard_demo
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
