# LSSGalPy: Interactive Visualization of the Large-scale Environment   Around Galaxies

**Authors:** M. Argudo-Fern\'andez, S. Duarte Puertas, J. E. Ruiz, J. Sabater, S., Verley, and G. Bergond

arXiv: 1702.04268 · 2017-04-26

## TL;DR

This paper introduces LSSGalPy, an open-source Python tool for interactive visualization of large-scale galaxy data and cosmic structures, facilitating data analysis in astrophysics.

## Contribution

The authors developed and released flexible, interactive Python tools for visualizing large 3D galaxy datasets with customizable projections and widgets.

## Key findings

- Handles millions of objects efficiently
- Provides interactive Mollweide and wedge diagram visualizations
- Open-source and easily customizable for the scientific community

## Abstract

New tools are needed to handle the growth of data in astrophysics delivered by recent and upcoming surveys. We aim to build open-source, light, flexible, and interactive software designed to visualize extensive three-dimensional (3D) tabular data. Entirely written in the Python language, we have developed interactive tools to browse and visualize the positions of galaxies in the universe and their positions with respect to its large-scale structures (LSS). Motivated by a previous study, we created two codes using Mollweide projection and wedge diagram visualizations, where survey galaxies can be overplotted on the LSS of the universe. These are interactive representations where the visualizations can be controlled by widgets. We have released these open-source codes that have been designed to be easily re-used and customized by the scientific community to fulfill their needs. The codes are adaptable to other kinds of 3D tabular data and are robust enough to handle several millions of objects.

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/1702.04268/full.md

## References

26 references — full list in the complete paper: https://tomesphere.com/paper/1702.04268/full.md

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Source: https://tomesphere.com/paper/1702.04268