This technical note describes the Python package SUNDARA (SUNDish Active Region Analyser), a sophisticated code - fully self-consistent - aimed at the data analysis of solar images.
This analysis is crucial for the INAF Proposal "SunDish Project" (PI: A. Pellizzoni), active since 2018 and devoted to imaging and monitoring the solar atmosphere at high radio frequencies (at present 18 - 26 GHz) through single-dish observations with INAF radio telescopes (SRT and Medicina).
SUNDARA, characterised by a very user-friendly widget, allows to automatically unearth Active Regions (ARs) across the solar disk (or on its edge) through several algorithms; these ARs are modelled through an elliptical 2D-Gaussian kernel.
In little more than 5 minutes, SUNDARA produces a complete analysis of a solar map, saving a directory containing images, plots and several tables with physical information of the solar disk and ARs (brightness temperatures, fluxes and spectral indices, with respective errors).
A deeper analysis (that can be completed in a few hours) is possible thanks to a Bayesian approach based on Markov Chain MonteCarlo (MCMC) simulations.
Moreover, these identified ARs are automatically associate in position with the detected ARs at other observing frequencies, reported in the Heliophysics Event Knowledgebase (HEK) used by the astrophysics and solar physics communities.
SUNDARA has been successfully tested on a large amount of data from solar maps implemented with the radio telescopes of the INAF Network.
For the purposes of this technical note, we report only two cases (one for Medicina, and one for SRT).
This Python package constitutes a crucial tool for the INAF Network to analyse solar images (the Space Weather monitoring network and forecast along the solar cycle will be soon available), and to provide a complete overview of the astrophysical phenomena
