drive-casa 0.4.0

Rationale

Casapy makes use of an altered version of IPython to provide a user interface, and all of the routines available are in fact python functions. This means it is possible to write python scripts and run them from within casapy itself. However, there are some compelling reasons not to do so:

• Casapy comes bundled with its very own python installation - version 2.6, in fact. This is getting pretty long in the tooth, and means that any code written elsewhere for 2.7 will need to be compatibility tested for 2.6, before running it under casapy.

• The ‘bundled installation’ model also means that setting up a virtualenv to run casa scripts in is effectively impossible, thus preventing well encapsulated and reproducible data-reduction environments.

• Casapy tasks do not, AFAICT, return any useful values. Rather, since the over-riding assumption is that the package will be run in interactive mode, all information is written to stderr as part of the logging output. While this cannot generally be solved by an external scripting interface, the specific issue of errors can be handled more gracefully - by parsing the log output for ‘SEVERE’ warnings we can choose to throw an exception when it is sensible to do so.

• If scripting the reduction of large amounts of data in batches, it is often useful to record logging information along with the data output, both for purposes of debugging and data provenance. AFAICT, Casapy does not provide an interface to control or redirect the logging output once the program has been instantiated. We can sidestep this problem by interfacing via the command line, and simply restarting casapy with a fresh logging location specified for each dataset.

Status

This package is still in the alpha stage - as such the interface may change in a backward incompatible manner without warning. However, if you think it could be of use to you, drop me a line.

Installation

Requirements:

• A working installation of casapy (naturally).

• pexpect (As listed in requirements.txt.)

From the command line (preferably within a virtualenv):

git clone git://github.com/timstaley/drive-casa.git
cd drive-casa
pip install numpy #Workaround for buggy scipy/numpy combined install.
pip install .

Documentation

Bare-bones Sphinx-generated documentation can be found at http://drive-casa.readthedocs.org.

A Brief Example

Basic usage might go something like this:

import drivecasa
casa = drivecasa.Casapy()
script=[]
uvfits_path = '/path/to/uvdata.fits'
vis = drivecasa.commands.import_uvfits(script, uvfits_path)
clean_args = {
    "spw": '0:3~7',
    "imsize": [512, 512],
    "cell": ['5.0arcsec'],
    "weighting": 'briggs',
       "robust": 0.5,
    }
dirty_maps = drivecasa.commands.clean(script, vis, niter=0, threshold_in_jy=1,
                                      other_clean_args=clean_args)
dirty_map_fits_image = drivecasa.commands.export_fits(script, dirty_maps['image'])
casa.run_script(script)

After which, there should be a dirty map converted to FITS format waiting for you.