LSST Applications 27.0.0,g0265f82a02+469cd937ee,g02d81e74bb+21ad69e7e1,g1470d8bcf6+cbe83ee85a,g2079a07aa2+e67c6346a6,g212a7c68fe+04a9158687,g2305ad1205+94392ce272,g295015adf3+81dd352a9d,g2bbee38e9b+469cd937ee,g337abbeb29+469cd937ee,g3939d97d7f+72a9f7b576,g487adcacf7+71499e7cba,g50ff169b8f+5929b3527e,g52b1c1532d+a6fc98d2e7,g591dd9f2cf+df404f777f,g5a732f18d5+be83d3ecdb,g64a986408d+21ad69e7e1,g858d7b2824+21ad69e7e1,g8a8a8dda67+a6fc98d2e7,g99cad8db69+f62e5b0af5,g9ddcbc5298+d4bad12328,ga1e77700b3+9c366c4306,ga8c6da7877+71e4819109,gb0e22166c9+25ba2f69a1,gb6a65358fc+469cd937ee,gbb8dafda3b+69d3c0e320,gc07e1c2157+a98bf949bb,gc120e1dc64+615ec43309,gc28159a63d+469cd937ee,gcf0d15dbbd+72a9f7b576,gdaeeff99f8+a38ce5ea23,ge6526c86ff+3a7c1ac5f1,ge79ae78c31+469cd937ee,gee10cc3b42+a6fc98d2e7,gf1cff7945b+21ad69e7e1,gfbcc870c63+9a11dc8c8f
LSST Data Management Base Package
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verifyWcs.py
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2# LSST Data Management System
3# Copyright 2008, 2009, 2010 LSST Corporation.
4#
5# This product includes software developed by the
6# LSST Project (http://www.lsst.org/).
7#
8# This program is free software: you can redistribute it and/or modify
9# it under the terms of the GNU General Public License as published by
10# the Free Software Foundation, either version 3 of the License, or
11# (at your option) any later version.
12#
13# This program is distributed in the hope that it will be useful,
14# but WITHOUT ANY WARRANTY; without even the implied warranty of
15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16# GNU General Public License for more details.
17#
18# You should have received a copy of the LSST License Statement and
19# the GNU General Public License along with this program. If not,
20# see <http://www.lsstcorp.org/LegalNotices/>.
21#
22
23__all__ = ["checkMatches"]
24
25
26import numpy as np
27import logging
28
29import lsst.geom
30import lsst.afw.detection as afwDetection
31import lsst.afw.math as afwMath
32import lsst.meas.algorithms as measAlg
33
34_LOG = logging.getLogger(__name__)
35
36
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
checkMatches(srcMatchSet, exposure, log=None)
Definition verifyWcs.py:37