LSST Applications
21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
LSST Data Management Base Package
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Public Member Functions | |
def | fitWcs (self, matches, initWcs, bbox=None, refCat=None, sourceCat=None, exposure=None) |
def | initialWcs (self, matches, wcs) |
def | rejectMatches (self, matches, wcs, rejected) |
def | plotFit (self, matches, wcs, rejected) |
Static Public Attributes | |
ConfigClass = FitTanSipWcsConfig | |
Fit a TAN-SIP WCS given a list of reference object/source matches.
Definition at line 74 of file fitTanSipWcs.py.
def lsst.meas.astrom.fitTanSipWcs.FitTanSipWcsTask.fitWcs | ( | self, | |
matches, | |||
initWcs, | |||
bbox = None , |
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refCat = None , |
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sourceCat = None , |
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exposure = None |
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) |
Fit a TAN-SIP WCS from a list of reference object/source matches Parameters ---------- matches : `list` of `lsst.afw.table.ReferenceMatch` The following fields are read: - match.first (reference object) coord - match.second (source) centroid The following fields are written: - match.first (reference object) centroid, - match.second (source) centroid - match.distance (on sky separation, in radians) initWcs : `lsst.afw.geom.SkyWcs` initial WCS bbox : `lsst.geom.Box2I` the region over which the WCS will be valid (an lsst:afw::geom::Box2I); if None or an empty box then computed from matches refCat : `lsst.afw.table.SimpleCatalog` reference object catalog, or None. If provided then all centroids are updated with the new WCS, otherwise only the centroids for ref objects in matches are updated. Required fields are "centroid_x", "centroid_y", "coord_ra", and "coord_dec". sourceCat : `lsst.afw.table.SourceCatalog` source catalog, or None. If provided then coords are updated with the new WCS; otherwise only the coords for sources in matches are updated. Required fields are "slot_Centroid_x", "slot_Centroid_y", and "coord_ra", and "coord_dec". exposure : `lsst.afw.image.Exposure` Ignored; present for consistency with FitSipDistortionTask. Returns ------- result : `lsst.pipe.base.Struct` with the following fields: - ``wcs`` : the fit WCS (`lsst.afw.geom.SkyWcs`) - ``scatterOnSky`` : median on-sky separation between reference objects and sources in "matches" (`lsst.afw.geom.Angle`)
Definition at line 81 of file fitTanSipWcs.py.
def lsst.meas.astrom.fitTanSipWcs.FitTanSipWcsTask.initialWcs | ( | self, | |
matches, | |||
wcs | |||
) |
Generate a guess Wcs from the astrometric matches We create a Wcs anchored at the center of the matches, with the scale of the input Wcs. This is necessary because matching returns only matches with no estimated Wcs, and the input Wcs is a wild guess. We're using the best of each: positions from the matches, and scale from the input Wcs. Parameters ---------- matches : `list` of `lsst.afw.table.ReferenceMatch` List of sources matched to references. wcs : `lsst.afw.geom.SkyWcs` Current WCS. Returns ------- newWcs : `lsst.afw.geom.SkyWcs` Initial WCS guess from estimated crpix and crval.
Definition at line 182 of file fitTanSipWcs.py.
def lsst.meas.astrom.fitTanSipWcs.FitTanSipWcsTask.plotFit | ( | self, | |
matches, | |||
wcs, | |||
rejected | |||
) |
Plot the fit We create four plots, for all combinations of (dx, dy) against (x, y). Good points are black, while rejected points are red. Parameters ---------- matches : `list` of `lsst.afw.table.ReferenceMatch` List of sources matched to references. wcs : `lsst.afw.geom.SkyWcs` Fitted WCS. rejected : array-like of `bool` Array of matches rejected from the fit.
Definition at line 262 of file fitTanSipWcs.py.
def lsst.meas.astrom.fitTanSipWcs.FitTanSipWcsTask.rejectMatches | ( | self, | |
matches, | |||
wcs, | |||
rejected | |||
) |
Flag deviant matches We return a boolean numpy array indicating whether the corresponding match should be rejected. The previous list of rejections is used so we can calculate uncontaminated statistics. Parameters ---------- matches : `list` of `lsst.afw.table.ReferenceMatch` List of sources matched to references. wcs : `lsst.afw.geom.SkyWcs` Fitted WCS. rejected : array-like of `bool` Array of matches rejected from the fit. Unused. Returns ------- rejectedMatches : `ndarray` of type `bool` Matched objects found to be outside of tolerance.
Definition at line 235 of file fitTanSipWcs.py.
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static |
Definition at line 77 of file fitTanSipWcs.py.