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
83
84
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
116
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])
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.