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LSST Applications g0000d66e7c+4a51730b0a,g0485b4d2cb+be65c9c1d7,g0fba68d861+eb108e5914,g1ec0fe41b4+3ea9d11450,g1fd858c14a+41d169aaf2,g2440f9efcc+8c5ae1fdc5,g35bb328faa+8c5ae1fdc5,g470b45d79c+bb7d8e732a,g4d2262a081+972b13e66a,g53246c7159+8c5ae1fdc5,g55585698de+c657de43f9,g56a49b3a55+7eddd92ad8,g60b5630c4e+c657de43f9,g67b6fd64d1+97cc007aa2,g78460c75b0+7e33a9eb6d,g786e29fd12+668abc6043,g7ac00fbb6c+088e1a4fa9,g8352419a5c+8c5ae1fdc5,g8852436030+3f3bba821f,g89139ef638+97cc007aa2,g94187f82dc+c657de43f9,g989de1cb63+97cc007aa2,g9d31334357+c657de43f9,g9f33ca652e+06d39d8afb,ga815be3f0b+8e7c4d07ad,gabe3b4be73+8856018cbb,gabf8522325+977d9fabaf,gb1101e3267+12c96a40b1,gb89ab40317+97cc007aa2,gc91f06edcd+2ffb87f22b,gcf25f946ba+3f3bba821f,gd6cbbdb0b4+1cc2750d2e,gde0f65d7ad+4ad7118dbf,ge278dab8ac+6b863515ed,ge410e46f29+97cc007aa2,gf35d7ec915+97dd712d81,gf5e32f922b+8c5ae1fdc5,gf67bdafdda+97cc007aa2,w.2025.19
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lsst.meas.astrom.verifyWcs Namespace Reference

Functions

 checkMatches (srcMatchSet, exposure, log=None)
 

Variables

 _LOG = logging.getLogger(__name__)
 

Function Documentation

◆ checkMatches()

lsst.meas.astrom.verifyWcs.checkMatches ( srcMatchSet,
exposure,
log = None )
Check astrometric matches and assess Wcs quality by computing statics
over spacial cells in the image.

Parameters
----------
srcMatchSet : `list` of `lsst.afw.table.ReferenceMatch`
    List of matched sources to a reference catalog.
exposure : `lsst.afw.image.Exposure`
    Image the sources in srcMatchSet were detected/measured in.
log : `lsst.log.Log` or `logging.Logger`
    Logger object.

Returns
-------
values : `dict`
    Result dictionary with fields:

    - ``minObjectsPerCell`` : (`int`)
    - ``maxObjectsPerCell`` : (`int`)
    - ``meanObjectsPerCell`` : (`float`)
    - ``stdObjectsPerCell`` : (`float`)

Definition at line 37 of file verifyWcs.py.

37def checkMatches(srcMatchSet, exposure, log=None):
38 """Check astrometric matches and assess Wcs quality by computing statics
39 over spacial cells in the image.
40
41 Parameters
42 ----------
43 srcMatchSet : `list` of `lsst.afw.table.ReferenceMatch`
44 List of matched sources to a reference catalog.
45 exposure : `lsst.afw.image.Exposure`
46 Image the sources in srcMatchSet were detected/measured in.
47 log : `lsst.log.Log` or `logging.Logger`
48 Logger object.
49
50 Returns
51 -------
52 values : `dict`
53 Result dictionary with fields:
54
55 - ``minObjectsPerCell`` : (`int`)
56 - ``maxObjectsPerCell`` : (`int`)
57 - ``meanObjectsPerCell`` : (`float`)
58 - ``stdObjectsPerCell`` : (`float`)
59 """
60 if not exposure:
61 return {}
62
63 if log is None:
64 log = _LOG
65
66 im = exposure.getMaskedImage().getImage()
67 width, height = im.getWidth(), im.getHeight()
68 nx, ny = 3, 3
69 w, h = width//nx, height//ny
70
71 if w == 0:
72 w = 1
73 while nx*w < width:
74 w += 1
75
76 if h == 0:
77 h = 1
78 while ny*h < height:
79 h += 1
80
81 cellSet = afwMath.SpatialCellSet(
82 lsst.geom.Box2I(lsst.geom.Point2I(0, 0), lsst.geom.Extent2I(width, height)), w, h)
83 #
84 # Populate cellSet
85 #
86 i = -1
87 for m in srcMatchSet:
88 i += 1
89
90 src = m.second
91 csrc = afwDetection.Source()
92 csrc.setId(i)
93 csrc.setXAstrom(src.getXAstrom())
94 csrc.setYAstrom(src.getYAstrom())
95
96 try:
97 cellSet.insertCandidate(measAlg.PsfCandidateF(csrc, exposure.getMaskedImage()))
98 except Exception as e:
99 log.warning("%s", e)
100
101 ncell = len(cellSet.getCellList())
102 nobj = np.ndarray(ncell, dtype='i')
103
104 for i in range(ncell):
105 cell = cellSet.getCellList()[i]
106
107 nobj[i] = cell.size()
108
109 dx = np.ndarray(cell.size())
110 dy = np.ndarray(cell.size())
111
112 j = 0
113 for cand in cell:
114 #
115 # Swig doesn't know that we're a SpatialCellImageCandidate; all it knows is that we have
116 # a SpatialCellCandidate so we need an explicit (dynamic) cast
117 #
118 mid = cand.getSource().getId()
119 dx[j] = srcMatchSet[mid].first.getXAstrom() - srcMatchSet[mid].second.getXAstrom()
120 dy[j] = srcMatchSet[mid].first.getYAstrom() - srcMatchSet[mid].second.getYAstrom()
121
122 j += 1
123
124 log.debug("%s %-30s %8s dx,dy = %5.2f,%5.2f rms_x,y = %5.2f,%5.2f",
125 cell.getLabel(), cell.getBBox(), ("nobj=%d" % cell.size()),
126 dx.mean(), dy.mean(), dx.std(), dy.std())
127
128 nobj.sort()
129
130 values = {}
131 values["minObjectsPerCell"] = int(nobj[0]) # otherwise it's a numpy integral type
132 values["maxObjectsPerCell"] = int(nobj[-1])
133 values["meanObjectsPerCell"] = nobj.mean()
134 values["stdObjectsPerCell"] = nobj.std()
135
136 return values
A collection of SpatialCells covering an entire image.
An integer coordinate rectangle.
Definition Box.h:55

Variable Documentation

◆ _LOG

lsst.meas.astrom.verifyWcs._LOG = logging.getLogger(__name__)
protected

Definition at line 34 of file verifyWcs.py.