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J plots classifies and quantifies a pixelated structure, based on its principal moments of inertia, thus enabling automatic detection and objective comparisons of centrally concentrated structures (cores), elongated structures (filaments) and hollow circular structures (bubbles) from the main population of slightly irregular blobs that make up most astronomical images. Examples of how to analyze 2D or 3D datasets, enabling an unbiased analysis and comparison of simulated and observed structures are provided along with the Python code.
RJ-plots uses a moments of inertia method to disentangle a 2D structure's elongation from its centrally over/under-density, thus providing a means for the automated and objective classification of such structures. It may be applied to any 2D pixelated image such as column density maps or moment zero maps of molecular lines. This method is a further development of J-plots (ascl:2009.007).