LSSTApplications  10.0-2-g4f67435,11.0.rc2+1,11.0.rc2+12,11.0.rc2+3,11.0.rc2+4,11.0.rc2+5,11.0.rc2+6,11.0.rc2+7,11.0.rc2+8
LSSTDataManagementBasePackage
sourceMatchStatistics.py
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1 #
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
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13 # This program is distributed in the hope that it will be useful,
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15 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16 # GNU General Public License for more details.
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21 #
22 
23 
24 import numpy as np
25 
26 def sourceMatchStatistics(matchList, log=None):
27  """ Compute statistics on the accuracy of a wcs solution, using a precomputed list
28  of matches between an image and a catalogue
29 
30  Input:
31  matchList is a lsst::afw::detection::SourceMatch object
32 
33  Output:
34  A dictionary storing the following quanities
35  meanOfDiffInPixels Average distance between image and catalogue position (in pixels)
36  rmsOfDiffInPixels Root mean square of distribution of distances
37  quartilesOfDiffInPixels An array of 5 values giving the boundaries of the quartiles of the
38  distribution.
39  """
40 
41  size = len(matchList)
42  if size == 0:
43  raise ValueError("matchList contains no elements")
44 
45  dist = np.zeros(size)
46  i = 0
47  for match in matchList:
48  catObj = match.first
49  srcObj = match.second
50 
51  cx = catObj.getXAstrom()
52  cy = catObj.getYAstrom()
53 
54  sx = srcObj.getXAstrom()
55  sy = srcObj.getYAstrom()
56 
57  dist[i] = np.hypot(cx-sx, cy-sy)
58  i = i+1
59 
60  dist.sort()
61 
62  quartiles = []
63  for f in (0.25, 0.50, 0.75):
64  i = int(f*size + 0.5)
65  if i >= size:
66  i = size - 1
67  quartiles.append(dist[i])
68 
69  values = {}
70  values['diffInPixels_Q25'] = quartiles[0]
71  values['diffInPixels_Q50'] = quartiles[1]
72  values['diffInPixels_Q75'] = quartiles[2]
73  values['diffInPixels_mean'] = dist.mean()
74  values['diffInPixels_std'] = dist.std()
75 
76  return values
77