The spectral-cube package provides an easy way to read, manipulate, analyze, and write data cubes with two positional dimensions and one spectral dimension, optionally with Stokes parameters. It provides the following main features: A uniform interface to spectral cubes, robust to the wide range of conventions of axis order, spatial projections, and spectral units that exist in the wild. Easy extraction of cube sub-regions using physical coordinates. Ability to easily create, combine, and apply masks to datasets. Basic summary statistic methods like moments and array aggregates. Designed to work with datasets too large to load into memory.
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References in zbMATH (referenced in 1 article )
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- Eric W. Koch, Ryan D. Boyden, Blakesley Burkhart, Adam Ginsburg, Jason L. Loeppky, Stella S.R. Offner: TurbuStat: Turbulence Statistics in Python (2019) arXiv