Compute and plot CTA IRFs
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. Or you can run a simple one here:
- Code : https://github.com/cta-observatory/ctaplot
- Documentation : https://ctaplot.readthedocs.io/en/latest/
- Author contact: Thomas Vuillaume - email@example.com
- 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.”
- python > 3.6
We recommend the use of anaconda
The package is available through pip:
pip install ctaplot
We recommend that you add this line to your bash source file ($HOME/.bashrc or $HOME/.bash_profile)
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.
To launch the dashboard, you can simply try the command:
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.
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.
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