MatchOptimisticBTask#

MatchOptimisticBTask matches sources to reference objects. This is often done as a preliminary step to fitting an astrometric or photometric solution.

Optimistic Pattern Matching is described in [Tabur2007]

Processing summary#

MatchOptimisticBTask runs this sequence of operations:

  • Flags sources with bad centroids and low signal to noise and remove them from the matching.

  • Match the usable sources with an input reference catalog using the V. Tabur 2007 algorithm.

  • Further remove sources detected on the edge of the image and those that are saturated.

  • Return these sources matched to the references.

Python API summary#

Retargetable subtasks#

Configuration fields#

Debugging#

The lsst.pipe.base.cmdLineTask.CmdLineTask command line task interface supports a flag -d to import debug.py from your PYTHONPATH; see lsstDebug for more about debug.py files.

The available variables in MatchOptimisticB are

display (bool)

If True display information at three stages: after finding reference objects, after matching sources to reference objects, and after fitting the WCS; defaults to False

frame (int)

frame to use to display the reference objects; the next two frames are used to display the match list and the results of the final WCS; defaults to 0

To investigate the meas_astrom_astrometry_Debug, put something like

import lsstDebug
def DebugInfo(name):
    debug = lsstDebug.getInfo(name) # N.b. lsstDebug.Info(name) would call us recursively
    if name == "lsst.meas.astrom.astrometry":
        debug.display = True

    return debug

lsstDebug.Info = DebugInfo

into your debug.py file and run this task with the --debug flag.