Sign in
Ctrl K

TraP: The LOFAR Transients Pipeline

The LOFAR Transients Pipeline (or "TraP") is a Python and SQL based system for detecting and responding to transient and variable sources in a stream of astronomical images.

Get started
1777 commits | Last commit 12 months ago

What TraP: The LOFAR Transients Pipeline can do for you

The LOFAR Transients Pipeline (“TraP”) provides a means of searching a stream of N-dimensional (two spatial, frequency, polarization) image “cubes” for transient astronomical sources. The pipeline was developed specifically to address data produced by the LOFAR Transients Key Science Project, but is also applicable to a range of other instruments.

The TraP codebase provides the pipeline definition itself, as well as a number of supporting routines for source finding, measurement, characterization, and so on. Some of these routines are also available as stand-alone tools.

Key features

  • Customisable ‘quality-control’ steps to weed out bad images before processing.
  • Built-in sourcefinder optimized for radio-synthesis images.
  • Optional source-fitting constraints (only fit point-sources, avoid fitting sources near to edge of image, etc).
  • Source-association incorporates knowledge of positional errors (using the DeRuiter radius algorithm) - this means much less trial-and-error tweaking of source-association parameters when working with a new dataset.
  • ‘Skyregion’ tracking - this keeps a record of which parts of sky have been previously surveyed, and to what faint limit, allowing for better separation of real transients and marginal steady-source detections.
  • Variability metrics and cataloguing for every source - no need to choose transient-detection thresholds ahead of time, simply sort through the data after processing and judge for yourself.
  • Position monitoring and null-detection tracking. ‘Forced’ source-fits are attempted at positions where a source has been previously detected, or where a monitoring location has been manually specified, allowing for better detection of sources near to the faint limit.
  • All source measurements are stored in a standard SQL database; users can write their own custom data-extraction and analysis tools if desired.
  • Ready-made web-based data-exploration interface. TraP is accompanied by Banana, a web-based tool which allows astronomers to sort and search source-catalogues without requiring any local installation or programming. Provides interactive plots, links to external catalogue searches, and more.
  • Support for multiple data formats and telescopes. TraP can process both FITS and CASA MeasurementSet formats, and it is usually quite straightforward to add support for a new telescope.


Participating organisations

University of Amsterdam
Netherlands eScience Center
Natural Sciences & Engineering
Natural Sciences & Engineering



Related projects

PADRE - The PetaFLOP AARTFAAC Data-Reduction Engine

Improving the AARTFAAC processing pipeline

Updated 2 months ago