Installation should be straightforward. A prepackage python system such as Anaconda https://www.anaconda.com is usually best as a base.

# Use git to make a local clone of the Github respository:

git clone https://github.com/SKA-ScienceDataProcessor/algorithm-reference-library

# Change into that directory:

cd algorithm-reference-library

# Install required python package:

pip install -r requirements.txt

# Setup ARL:

python setup.py install

# Get the data files form Git LFS:

git-lfs pull

The best way to run ARL is via jupyter notebooks. For example:

jupyter-notebook imaging.ipynb

See the jupyter note books below:

.. toctree::
   :maxdepth: 3

   arl/imaging
   arl/imaging-fits
   arl/imaging-wterm
   arl/imaging-mfs
   arl/imaging-spectral
   arl/rcal
   arl/peeling
   arl/simple-dask

In addition, there are other notebooks in examples/arl that are not built as part of this documentation.