Version: 0.4.2.dev88+gd16544460 | Date: Nov 11, 2025
Useful links: Source Repository | Issue Tracker | Pull Requests
License: MIT
Python: >=3.11
radionets is a deep-learning framework for the simulation and analysis of radio interferometric data in Python.
The goal is to reconstruct calibrated observations with convolutional Neural Networks to create
high-resolution images. For further information, please have a look at our
paper.
Analysis strategies leading to reproducible processing and evaluation of data recorded by radio interferometers include:
Simulation of datasets (see also the radionets-project/radiosim repository)
Simulation of radio interferometer observations (see also the radionets-project/pyvisgen repository)
Training of deep learning models
Reconstruction of radio interferometric data
User Guide
Learn how to get started as a user. This guide will help you install radionets.
Developer Guide
Learn how to get started as a developer. This guide will help you install radionets for development and explains how to contribute.
API Docs
The API docs contain detailed descriptions of of the various modules, classes and functions included in radionets.