ClassiPyGRB is a Python 3 package to download, process, visualize and classify Gamma-Ray-Bursts (GRBs) from the Swift/BAT Telescope (https://swift.gsfc.nasa.gov/about_swift/bat_desc.html) database. It is distributed over the GNU General Public License Version 2 (1991). Please, read the complete description of the method and its application to GRBs in this publication.

Attribution

If you use this code in a publication, please refer to the package by its name and cite Garcia-Cifuentes et al.(2023) -> arXiv link. Any question, please email Keneth Garcia-Cifuentes.

Dependencies

This repository requires Python 3.8 or high, and a list of packages downloaded automatically (numpy, scikit-learn, etc). In addition, it is required to install all the dependencies related to Tkinter, Pillow, and ImageTK. In Debian-based distros you can install these packages by running the following commands:

$ sudo apt-get install python3-tk
$ sudo apt-get install python3-pil python3-pil.imagetk

Other data management packages as Numpy or Pandas will be required in Documentation.

Installation

The latest sources from ClassiPyGRB are avaiable by cloning the repository:

$ git clone https://github.com/KenethGarcia/ClassiPyGRB
$ cd ClassiPyGRB
$ pip install .

Or, using pip:

$ pip install ClassiPyGRB@git+https://github.com/KenethGarcia/ClassiPyGRB

or by using the stable PyPI compiled version:

$ pip install ClassiPyGRB

Features

In ClassiPyGRB, it is possible to retrieve data from the Swift/BAT catalog by a three-line code:

from ClassiPyGRB import SWIFT
swift = SWIFT(res=64)
df = swift.obtain_data(name='GRB211211A')

Moreover, you can plot a light curve using one single line:

swift.plot_any_grb(name='GRB060614')

You can do specialized tasks to see the convergence of t-Distributed Stochastic Neighbor Embedding (TSNE):

or use a Graphical User Interface (GUI) to analyze the embeddings obtained by TSNE:

We strongly encourage you to read the Documentation of ClassiPyGRB before start. This documentation includes all the details and follow-up for managing and processing data from Swift/BAT, performing TSNE, plotting and animating their results, and how to use the internal GUI. Moreover, we developed intuitive notebooks to support you in your research.

• 1. Basic Usage
• 2. BAT: Data_Download
• 3. BAT: Preprocess
• 4. BAT: Noise_Reduction
• 5. BAT: Interpolation
• 6. TSNE: Introduction
• 7. TSNE: Overview
• 8. Plotting with t-SNE
• 9. Clustering Properties
• 10. Applications and Example
• 11. Internal GUI

Enhancement and Support

ClassiPyGRB is a open-source package where all kinds of contributions are welcome. Whether you want to report a bug or submit a pull request, your feedback, comments and suggestions will be very welcome.

Here are some ways you can get involved in this project:

• Report a bug or issue on our GitHub Issues page.
• Suggest a new feature or improvement by opening a new issue.
• Submit a pull request with your code changes or enhancements.
• Share ClassiPyGRB on social media or with your colleagues.

We appreciate your interest in this package. Please, do not hesitate to email Keneth Garcia to discuss any topic related to ClassiPyGRB.