ctaplot

Plotting library for CTA and other IACT

https://github.com/cta-observatory/ctaplot

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 5 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
    1 of 5 committers (20.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Plotting library for CTA and other IACT

Basic Info
  • Host: GitHub
  • Owner: cta-observatory
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage: https://ctaplot.readthedocs.io
  • Size: 10.8 MB
Statistics
  • Stars: 7
  • Watchers: 8
  • Forks: 9
  • Open Issues: 6
  • Releases: 19
Created over 7 years ago · Last pushed 8 months ago
Metadata Files
Readme License Codemeta

README.rst

=======
ctaplot
=======

ctaplot provides low-level reconstruction quality-checks metrics computation and vizualisation for Imaging Atmospheric Cherenkov Telescopes such as CTA

.. 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
 
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5833854.svg
  :target: https://doi.org/10.5281/zenodo.5833853


You may find examples in the `documentation `_ and run them via mybinder.


----


* 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 `_ .

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.”

----


Install
=======


Requirements packages:

* python >= 3.9
* numpy  
* scipy>=0.19    
* matplotlib>=3.6
* astropy

Optional LaTeX dependencies for enhanced plot rendering:

* A LaTeX distribution (e.g., TeX Live, MiKTeX)
* dvipng (for PNG output)
* cm-super (Computer Modern fonts)

**Installation instructions:**

On Ubuntu/Debian:

.. code-block:: bash

   sudo apt-get install texlive-latex-base texlive-fonts-recommended dvipng cm-super

On macOS with Homebrew:

.. code-block:: bash

   brew install --cask mactex
   # dvipng and cm-super are included with MacTeX

On macOS with MacPorts:

.. code-block:: bash

   sudo port install texlive +full

**Note:** LaTeX dependencies are optional. If not installed, ctaplot will automatically 
fall back to matplotlib's default text rendering without LaTeX support.

We recommend the use of `anaconda `_

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 especially by the `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


Cite
====

We would appreciate you cite the version of ctaplot you used using the corresponding Zenodo DOI that cound find here: https://doi.org/10.5281/zenodo.5833853

Owner

  • Name: Cherenkov Telescope Array Consortium
  • Login: cta-observatory
  • Kind: organization

open-source software for the CTA Consortium.

CodeMeta (codemeta.json)

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "license": "https://spdx.org/licenses/MIT",
  "codeRepository": "https://github.com/cta-observatory/ctaplot.git",
  "contIntegration": "https://github.com/cta-observatory/ctaplot/actions",
  "dateCreated": "2018-07-06",
  "datePublished": "2025-10-07",
  "dateModified": "2025-10-07",
  "downloadUrl": "https://github.com/cta-observatory/ctaplot/archive/v0.6.5.zip",
  "issueTracker": "https://github.com/cta-observatory/ctaplot/issues",
  "name": "ctaplot",
  "version": "0.6.5",
  "description": "ctaplot provides low-level reconstruction quality-checks metrics computation and vizualisation for Imaging Atmospheric Cherenkov Telescopes such as CTA",
  "applicationCategory": "Astronomy",
  "releaseNotes": "Version 0.6.5. See changelog: https://github.com/cta-observatory/ctaplot/releases",
  "funding": "Grant 824064",
  "funder": {
    "@type": "Organization",
    "name": "European Unions Horizon 2020"
  },
  "keywords": [
    "astronomy"
  ],
  "programmingLanguage": [
    "Python 3"
  ],
  "softwareRequirements": [
    "Python>=3.6"
  ],
  "author": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0002-5686-2078",
      "givenName": "Thomas",
      "familyName": "Vuillaume",
      "email": "thomas.vuillaume@lapp.in2p3.fr",
      "affiliation": {
        "@type": "Organization",
        "name": "LAPP, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS-IN2P3"
      }
    }
  ],
  "contributor": [
    {
      "@type": "Person",
      "givenName": "Mikael",
      "familyName": "Jacquemont",
      "email": "mikael.jacquemont@lapp.in2p3.fr",
      "affiliation": {
        "@type": "Organization",
        "name": "LAPP, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS-IN2P3"
      }
    }
  ]
}

GitHub Events

Total
  • Issues event: 2
  • Watch event: 2
  • Delete event: 1
  • Push event: 1
  • Pull request event: 1
  • Create event: 1
Last Year
  • Issues event: 2
  • Watch event: 2
  • Delete event: 1
  • Push event: 1
  • Pull request event: 1
  • Create event: 1

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 570
  • Total Committers: 5
  • Avg Commits per committer: 114.0
  • Development Distribution Score (DDS): 0.309
Top Committers
Name Email Commits
vuillaut t****e@g****m 394
Vuillaume t****e@l****r 99
mikael m****t@l****r 72
Maximilian Nöthe m****e@t****e 4
Sebastián Bórquez s****g@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 30
  • Total pull requests: 83
  • Average time to close issues: about 1 year
  • Average time to close pull requests: about 1 month
  • Total issue authors: 8
  • Total pull request authors: 4
  • Average comments per issue: 0.97
  • Average comments per pull request: 0.75
  • Merged pull requests: 80
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 2
  • Average time to close issues: 30 minutes
  • Average time to close pull requests: 8 minutes
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • vuillaut (10)
  • mikael10j (8)
  • maxnoe (7)
  • sborquez (1)
  • TjarkMiener (1)
  • moralejo (1)
  • Tobychev (1)
  • BastienLacave (1)
Pull Request Authors
  • vuillaut (67)
  • mikael10j (14)
  • maxnoe (2)
  • sborquez (1)
Top Labels
Issue Labels
enhancement (6) bug (4)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 692 last-month
  • Total dependent packages: 4
  • Total dependent repositories: 9
  • Total versions: 13
  • Total maintainers: 1
pypi.org: ctaplot

Compute and plot CTA IRFs

  • Versions: 13
  • Dependent Packages: 4
  • Dependent Repositories: 9
  • Downloads: 692 Last month
Rankings
Dependent packages count: 2.3%
Dependent repos count: 4.9%
Average: 10.2%
Downloads: 10.8%
Forks count: 11.4%
Stargazers count: 21.5%
Maintainers (1)
Last synced: 7 months ago

Dependencies

docs/requirements.txt pypi
  • astropy *
  • ipywidgets *
  • jupyter *
  • matplotlib >=2.0
  • nbsphinx *
  • numpy >1.16
  • pandas *
  • recommonmark *
  • scikit-learn *
  • scipy >=0.19
  • sphinx >=4.2
  • sphinx_rtd_theme *
  • tables *
setup.py pypi
  • astropy *
  • ipympl *
  • ipywidgets *
  • jupyter *
  • matplotlib >=2.0
  • numpy >1.16
  • pandas *
  • pyyaml *
  • scikit-learn *
  • scipy >=0.19
  • tables *
  • tqdm *
.github/workflows/continuousintegration.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • codecov/codecov-action v1 composite
.github/workflows/pypi.yml actions
  • actions/checkout v2 composite
  • pypa/gh-action-pypi-publish release/v1 composite
environment.yml pypi