8000 JP-3509: Cut cube collapse for autocentroiding short of 26 microns by drlaw1558 · Pull Request #8199 · spacetelescope/jwst · GitHub
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JP-3509: Cut cube collapse for autocentroiding short of 26 microns #8199

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Merged
merged 2 commits into from
Jan 23, 2024
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JP-3509: Cut cube collapse for autocentroiding short of 26 microns #8199

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06bc477
Bugfix for JP-3509
drlaw1558 Jan 16, 2024
853e74e
Update changelog
drlaw1558 Jan 16, 2024
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4 changes: 4 additions & 0 deletions CHANGES.rst
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Expand Up @@ -28,6 +28,10 @@ extract_1d
- Fixed a bug in the calling of optional MIRI MRS 1d residual fringe
correction that could cause defringing to fail in some cases. [#8180]

- Fixed ifu auto-centroiding to only use wavelengths shortward of 26 microns
to avoid failures for moderate-brightness sources due to extremely low
throughput at the long wavelength end of MRS band 4C. [#8199]

tweakreg
--------

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3 changes: 2 additions & 1 deletion docs/jwst/extract_1d/arguments.rst
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Expand Up @@ -102,7 +102,8 @@ The ``extract_1d`` step has the following step-specific arguments.
``--ifu_autocen``
Switch to select whether or not to enable auto-centroiding of the extraction
aperture for IFU point sources. Auto-centroiding works by median collapsing the
IFU cube across all wavelengths and using DAOStarFinder to locate the brightest
IFU cube across all wavelengths (shortward of 26 microns where the MRS throughput
becomes extremely low) and using DAOStarFinder to locate the brightest
source in the field. Default is ``False``.

``--ifu_rfcorr``
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8 changes: 7 additions & 1 deletion jwst/extract_1d/ifu.py
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Expand Up @@ -504,7 +504,13 @@ def extract_ifu(input_model, source_type, extract_params):
# If ifu_autocen is set, try to find the source in the field using DAOphot
if extract_params['ifu_autocen'] is True:
log.info('Using auto source detection.')
collapse = np.ma.median(np.ma.masked_invalid(data), axis=0)

# Median collapse across wavelengths, but ignore wavelengths above
# 26 microns where MRS throughput is extremely low
(_, _, wavetemp) = get_coordinates(input_model, 1, 1)
indx = (np.where(wavetemp < 26))[0]
collapse = np.ma.median(np.ma.masked_invalid(data[indx, :, :]), axis=0)

# Sigma-clipped stats on collapsed image
_, clipmed, cliprms = sigclip(collapse)
# Find source in the collapsed image above 3 sigma
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