CoAdd2D now correctly uses manually extracted objects for offsets/weights#2092
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tbowers7 wants to merge 3 commits intopypeit:developfrom
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CoAdd2D now correctly uses manually extracted objects for offsets/weights#2092tbowers7 wants to merge 3 commits intopypeit:developfrom
tbowers7 wants to merge 3 commits intopypeit:developfrom
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In the Coadd2d process, the input images are rebinned and an attempt is made to refind objects. If the coadd is being done with very low-signal objects, it should be possible to manually extract objects at pre-defined locations and bypass the automated object finding. This is the first step in this direction. modified: pypeit/coadd2d.py modified: pypeit/core/coadd.py modified: pypeit/flatfield.py modified: pypeit/par/parset.py modified: pypeit/par/pypeitpar.py
For code development, add TEST logging level, between INFO and WARNING.
The combination of manual extraction of individual frames and use of the [coadd2d][user_obj_ids] parameter now correctly sets the offets and weights for the desired objects. This allows for manually extracted objects to be correctly coadded even when the object drifts along the slit during a series of exposures. modified: pypeit/coadd2d.py modified: pypeit/core/coadd.py modified: pypeit/core/findobj_skymask.py modified: pypeit/manual_extract.py
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TODO: Clean up the description...
In concert with the Coadd2DPar
user_obj_ids, this PR corrects the CoAdd2D code to pay attention to manually extracted objects when computing offsets and weights.Previously, the coadd2d process would do a full-on object finding, crashing if one of the input frames did not detect objects above the required S/N level. Even if the
user_obj_idsparameter was passed in, the coaddition would not pay attention to the desired object.This PR checks for the presence of
user_obj_idsand essentially performs a manual extraction at the location of the requested objects from this parameter for the purposes of computing offsets and weights only.In the final coadded frame, the object-finding follows the existing paradigm.
In a couple of places, dictionaries were replaced with either
@dataclassobjects or numpy arrays for clarity.Tests to follow.