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Overview

stimela (Stimela is the IsiZulu word for a train) is a platform independent radio interferometry scripting framework based on Docker and Python. In this framework, radio interferometry related tasks such as imaging, calibration and data synthesis are executed in Docker containers. In fact, within this framework the packages that perform these tasks are Python modules. Much like Oleg Smirnov's pyxis package, stimela does not do any data processing, synthesis or analysis but merely offers a simple interface to packages that perform these tasks. However, unlike pyxis which requires multiple radio astronomy packages to be working on the same system, stimela only requires Docker and Python. Moreover, because of Docker, a stimela script runs the same way (in the same isolated environment) regardless of the host machine's settings, and coupled with applications docker-machine, stimela opens up the window to flexible, easily scalable, and distributed data reduction and synthesis scripting (or pipelines).

The aim of stimela is to provide a user friendly and modular scripting environment that gives general users easy access to novel radio interferometry calibration, imaging, and synthesis packages.

Architecture

stimela is centred around two sets of Docker images, i) base images, which have the required software tools installed in them, and ii) very light weight executor images (a.k.a cab images) based on the base images, these perform radio interferometry related tasks like imaging, data synthesis, and calibration. The base images can either be built locally (on the host machine) or pulled from Docker hub, and the executor mages are built locally.

Base images

Base images are a suite of Docker images which have various radio astronomy related packages, including data synthesis and calibration packages such as CASA and MeqTrees, and imaging packages such as lwimager and wsclean. Base images are maintained by the {\tt Radio Astro} project on the Docker hub, but any Docker image can be used as a base image. These are the available base images:

• radioastro/meqtrees
• radioastro/lwimager
• radioastro/wsclean
• radioastro/simms
• radioastro/tigger
• radioastro/aoflagger
• radioastro/casa
• radioastro/sourcery

Executor images (a.k.a cab images)

These Docker images are generally pre-loaded with Python scripts that perform a specified task (e.g calibrating a visibility dataset). A stimela cab image takes some input as well a set of instructions, performs some task, then returns the output.

• cab/simms
• cab/simulator
• cab/calibrator
• cab/casa
• cab/lwimager
• cab/wsclean
• cab/tigger
• cab/specfit
• cab/sourcery
• cab/autoflagger
• cab/flagms