Skip to content
master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

MeerKAT-Cookbook

Recipes for MeerKAT data interaction and processing presented in CASA-Jupyter notebook format for easy interaction.
Usage and installation instruction for CASA-Jupyter can be found in Github

MeerKAT data is stored in a flexible format called MeerKAT Visibility Format (MVF), and accessed/processed as needed.
Easy access and software specifically developed to handle MeerKAT large data sizes are provided through the MeerKAT archive and katdal packages.

Important Notes:
If you are using the docker container to run the CASA-Jupyter notebooks, you will need to install katdal

  • run/start the docker container
  • enter the docker container as root: docker exec -tiu root container ID bash
  • install katdal: pip install katdal
  • for active notebooks, restart the notebook kernel (using the Kernel menu option)
  • running a cell with import katdal should now work

Note to reader
MeerKAT data files are large and combining the data for an observation using the full array into single files cause sizes of Giga- to Tera bytes. These files are to big for standard io-operations.

ARCHIVE

All MeerKAT data is accessed via the SARAO archive
Important Notes:

  • MeerKAT archive is access restricted, requiring registration and login
  • To access data in the MeerKAT archive a token is required.

User guideline to register, access and retrieve data from the archive are provided in the Archive Interface User Guide

Example notebooks showing data interaction and extraction methods can be found in the archive folder

If you are following standard interferometric imaging data reduction using CASA measurement sets, you can also use the Direct Download Link to create and download a measurement set instead.
See Archive Interface User Guide for detail.

KATDAL

Interacting with any of the MeerKAT observation files is made easy by the katdal python library
katdal repository Open source library available from PyPI

pip search katdal
katdal (0.13)  - Karoo Array Telescope data access library for interacting with data sets in the MeerKAT Visibility Format (MVF)

Easy install

pip install katdal

Positional astronomy calculation use the PyEphem library

Detail katdal documentation with user guide instructions can be found on the katdal User guide

katdal is specifically developed to allow efficient access to MeerKAT Visibility Format (MVF). It is fully integrated to access data via the katarchive line, optimised for large file data access and memory usage. Introductory Jupyter notebooks illustrating some example data interaction and inspection using katdal

Cutting edge functionality can be obtained by installing katdal directly from the GitHub repository

pip install git+https://github.com/ska-sa/katdal.git

Import Note Care should be taken since installing the master from GitHub might not be as stable as PyPI.

CASA

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.
Examples on how to create measurement sets from a user control environment using tokens from the archive are given in example notebooks in the utils folder.

Standard recipes for flagging and calibration are provided in the casa folder.

Notes

Plotting and planning tools 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-