Transform radio telescope data into stunning visualizations with Python - from 3D channel maps to rotatable HTML cubes, this astronomer-built package bridges the gap between raw FITS files and publication-ready figures.

Radio astronomy generates some of the universe’s most fascinating data - from the rotation curves of distant galaxies to the chemical fingerprints of star-forming regions. But transforming raw FITS files from radio telescopes into meaningful, publication-ready visualizations has long been a technical hurdle that separates astronomers from their discoveries. This is precisely the challenge that plotastrodata tackles head-on.

Built by astronomer Yusuke Aso, this Python package seamlessly integrates astropy’s robust data handling with matplotlib’s visualization prowess to create stunning scientific figures. Whether you’re crafting 3D channel maps that reveal gas kinematics across velocity space, generating interactive HTML cubes for presentations, or overlaying contours from different observations with varying spatial resolutions, plotastrodata handles the complex coordinate transformations and scaling automatically. The package supports everything from Gaussian line profile fitting to creating movies of evolving astronomical phenomena, complete with custom annotations, arrows, and regions of interest.

With support for multiple coordinate systems (RA-Dec or offset coordinates), flexible color scaling (linear, logarithmic, or asinh), and the ability to combine RGB imagery with contour maps, this tool empowers researchers to tell compelling visual stories with their data. From graduate students creating their first publication figures to seasoned astronomers building public outreach materials, plotastrodata democratizes high-quality astronomical visualization.

⭐ Stars: 3
💻 Language: Python
🔗 Repository: yusukeaso-astron/plotastrodata