Beginners guide for introducing and training using MeerKAT data
The cookbook forms part of the SARAO African Radio Interferometry Winter School (ARIWS)
The winter school can be found online via SARAO E-learning

Practical examples and tutorials uses Google COLAB and can be executed online.
Note: Data used in the tutorials must be uploaded to the notebooks during the processing runs

This notebook is for introduction purposes only, for more information please refer to the MeerKAT-Cookbook, available through the SARAO operational interface. The MeerKAT cookbook contains notebooks with detailed examples specifically focused to MeerKAT user interfacing, such as:

• How to interact with the SARAO archive MeerKAT-Cookbook/archive
• Using the MeerKAT katdal software to inspect, obtain and process MeerKAT data MeerKAT-Cookbook/katdal
• As well as some MeerKAT specific notebooks for observation planning MeerKAT-Cookbook/utility

Standard recipes for flagging and calibration
CASA MeasurementSet data tables can be created using a convenient helper script mvftoms.py available from katdal installation.
Measurement sets can be downloaded directly from the MeerKAT archive using some sensible defaults when created. MeerKAT operational Examples on how to create measurement sets from a user control environment using tokens from the archive are given in example notebooks in the archive folder of the MeerKAT-Cookbook.

Introductory notebooks to familiarise the user with radio astronomy concepts and methods.
All tutorials make extensive use of the matplotlib and astropy python libraries

pip install matplotlib
pip install astropy

Plotting the antenna location makes use of the mpl_toolkits.basemap functionality, which may be a little tricky to install.
Basemap installation requires libgeos. The following worked for the author

sudo apt-get install libgeos-3.6.2 libgeos-c1v5 libgeos-dev
git clone https://github.com/matplotlib/basemap.git
cd basemap/
pip install .

-fin-