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VisualAstro

visualastro is an astrophysical visualization system with functions for easy visualization and manipulation of common astronomical data. The package is developed with ease of use in mind, modularity, and making publication-ready plots with minimal commands.

Installation

Currently, the most stable version of python for visualastro is version >=3.10. To install visualastro, it is advised to create a new conda environment if possible:

$ conda create visualastro -c conda-forge python=3.14
$ conda activate visualastro

Then install the dependencies with:

$ conda install -c conda-forge \
    astropy dust_extinction matplotlib numpy regions reproject spectral-cube specutils scipy tqdm

For additional interactive functionality inside of jupyter lab:

$ conda install -c conda-forge ipympl ipywidgets jupyterlab

For classic jupyter notebook users:

$ conda install -c conda-forge ipympl ipywidgets notebook jupyter_server notebook-shim

And finally run:

$ pip install visualastro

NOTE: To ensure that interactive mode works in notebooks, first activate your conda environment and then run jupyter notebook!

Features

• Unified interface for matplotlib, astropy, numpy, spectral-cube, specutils, and other astronomy packages
• High-level wrappers of common functions and algorithms used in astrophysical research
• Custom matplotlib style sheets optimized for publication-quality figures
• Full compatibility with WCS, FITS, and astropy units

Documentation

Visualastro is still under development! A full documentation of the package's features is coming soon.

The full documentation can be found on github at https://github.com/elkogerville/VisualAstro

Dependencies

VisualAstro requires:

astropy, dust_extinction, matplotlib, numpy, regions, reproject, spectral-cube, specutils, scipy, tol_colors, and tqdm.

Credits

Fonts

VisualAstro includes Hershey-style TrueType fonts from the smplotlib project by Jiaxuan Li, used under the MIT License. Citation:

@software{jiaxuan_li_2023_8126529,
  author       = {Jiaxuan Li},
  title        = {AstroJacobLi/smplotlib: v0.0.9},
  month        = jul,
  year         = 2023,
  publisher    = {Zenodo},
  version      = {v0.0.9},
  doi          = {10.5281/zenodo.8126529},
  url          = {https://doi.org/10.5281/zenodo.8126529},
}