lsst.meas.astrom  16.0-4-g1a325e7+3
sourceMatchStatistics.py
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22 
23 __all__ = ["sourceMatchStatistics"]
24 
25 import numpy as np
26 
27 
28 def sourceMatchStatistics(matchList, log=None):
29  """Compute statistics on the accuracy of a wcs solution, using a precomputed list
30  of matches between an image and a catalogue
31 
32  Input:
33  matchList is a lsst::afw::detection::SourceMatch object
34 
35  Output:
36  A dictionary storing the following quanities
37  meanOfDiffInPixels Average distance between image and catalogue position (in pixels)
38  rmsOfDiffInPixels Root mean square of distribution of distances
39  quartilesOfDiffInPixels An array of 5 values giving the boundaries of the quartiles of the
40  distribution.
41  """
42 
43  size = len(matchList)
44  if size == 0:
45  raise ValueError("matchList contains no elements")
46 
47  dist = np.zeros(size)
48  i = 0
49  for match in matchList:
50  catObj = match.first
51  srcObj = match.second
52 
53  cx = catObj.getXAstrom()
54  cy = catObj.getYAstrom()
55 
56  sx = srcObj.getXAstrom()
57  sy = srcObj.getYAstrom()
58 
59  dist[i] = np.hypot(cx-sx, cy-sy)
60  i = i+1
61 
62  dist.sort()
63 
64  quartiles = []
65  for f in (0.25, 0.50, 0.75):
66  i = int(f*size + 0.5)
67  if i >= size:
68  i = size - 1
69  quartiles.append(dist[i])
70 
71  values = {}
72  values['diffInPixels_Q25'] = quartiles[0]
73  values['diffInPixels_Q50'] = quartiles[1]
74  values['diffInPixels_Q75'] = quartiles[2]
75  values['diffInPixels_mean'] = dist.mean()
76  values['diffInPixels_std'] = dist.std()
77 
78  return values