@@ -5,15 +5,17 @@ This repository provides a hands on tutorial to perform radio imaging using info
The demo scripts `nifty_interfaces.py` and `nifty_intro.py` give and introduction
into the world of nifty and how to do inference with it.
In addition, two Jupyter notebooks are available:
In addition, three Jupyter notebooks are available:
-`demo_CorrelatedFields.ipynb`: An introduction to the correlated field model, its hyperparameters, and their effect in the statistical properties of the gaussian process.
-`demo_radio.ipynb`: A mock inference task given a simplified VLBI imaging setup using the uv-coverage of the 2017 imaging campaign of the Event Horizon Telescope ([eht](https://eventhorizontelescope.org/)) and an artificially generated sky brightness distribution.
-`demo_joint_cal_imag.ipynb`: A resolve demo script for joint calibration and imaging. The demo uses VLA data of SN1006.
