lsst.meas.astrom  14.0-7-g0d69b06+3
sourceMatchStatistics.py
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22 from __future__ import absolute_import, division, print_function
23 
24 __all__ = ["sourceMatchStatistics"]
25 
26 import numpy as np
27 
28 
29 def sourceMatchStatistics(matchList, log=None):
30  """Compute statistics on the accuracy of a wcs solution, using a precomputed list
31  of matches between an image and a catalogue
32 
33  Input:
34  matchList is a lsst::afw::detection::SourceMatch object
35 
36  Output:
37  A dictionary storing the following quanities
38  meanOfDiffInPixels Average distance between image and catalogue position (in pixels)
39  rmsOfDiffInPixels Root mean square of distribution of distances
40  quartilesOfDiffInPixels An array of 5 values giving the boundaries of the quartiles of the
41  distribution.
42  """
43 
44  size = len(matchList)
45  if size == 0:
46  raise ValueError("matchList contains no elements")
47 
48  dist = np.zeros(size)
49  i = 0
50  for match in matchList:
51  catObj = match.first
52  srcObj = match.second
53 
54  cx = catObj.getXAstrom()
55  cy = catObj.getYAstrom()
56 
57  sx = srcObj.getXAstrom()
58  sy = srcObj.getYAstrom()
59 
60  dist[i] = np.hypot(cx-sx, cy-sy)
61  i = i+1
62 
63  dist.sort()
64 
65  quartiles = []
66  for f in (0.25, 0.50, 0.75):
67  i = int(f*size + 0.5)
68  if i >= size:
69  i = size - 1
70  quartiles.append(dist[i])
71 
72  values = {}
73  values['diffInPixels_Q25'] = quartiles[0]
74  values['diffInPixels_Q50'] = quartiles[1]
75  values['diffInPixels_Q75'] = quartiles[2]
76  values['diffInPixels_mean'] = dist.mean()
77  values['diffInPixels_std'] = dist.std()
78 
79  return values