  The data reduction procedure for radio interferometers can be viewed as a
combined calibration and imaging problem. We present an algorithm that unifies
cross-calibration, self-calibration, and imaging. Being a Bayesian method, that
algorithm does not only calculate an estimate of the sky brightness
distribution, but also provides an estimate of the joint uncertainty which
entails both the uncertainty of the calibration and the one of the actual
observation. The algorithm is formulated in the language of information field
theory and uses Metric Gaussian Variational Inference (MGVI) as the underlying
statistical method. So far only direction-independent antenna-based calibration
is considered. This restriction may be released in future work. An
implementation of the algorithm is contributed as well.
