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VisualAstro

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

Installation

Currently, the most stable version of python for visualastro is version 3.11. To install visualastro, it is advised to create a new conda environment if possible:

$ conda create envname -c conda-forge python=3.11
$ conda activate envname

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 notebooks:

$ 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 activate jupyter notebook!

Compatible Data

• 2D images
• 3D spectral cubes
• 1D spectra with gaussian fitting tools

Features

• Simple, high-level wrapper functions for common astrophysical plots
• Custom matplotlib style sheets optimized for publication-quality figures
• Full compatibility with WCS, FITS

Documentation

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

Dependencies

VisualAstro requires:

astropy, dust_extinction, matplotlib, regions, reproject, spectral-cube, specutils, scipy, 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},
}