Coverage for python/lsst/meas/astrom/denormalizeMatches.py: 11%

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1# This file is part of meas_astrom. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (https://www.lsst.org). 

6# See the COPYRIGHT file at the top-level directory of this distribution 

7# for details of code ownership. 

8# 

9# This program is free software: you can redistribute it and/or modify 

10# it under the terms of the GNU General Public License as published by 

11# the Free Software Foundation, either version 3 of the License, or 

12# (at your option) any later version. 

13# 

14# This program is distributed in the hope that it will be useful, 

15# but WITHOUT ANY WARRANTY; without even the implied warranty of 

16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

17# GNU General Public License for more details. 

18# 

19# You should have received a copy of the GNU General Public License 

20# along with this program. If not, see <https://www.gnu.org/licenses/>. 

21 

22__all__ = ["denormalizeMatches"] 

23 

24import lsst.afw.table as afwTable 

25 

26 

27def denormalizeMatches(matches, matchMeta=None): 

28 """Generate a denormalized Catalog of matches 

29 

30 Parameters 

31 ---------- 

32 matches : `list` of `lsst.afw.table.ReferenceMatch` 

33 List of matches between reference catalog and source catalog. 

34 matchMeta : `lsst.daf.base.PropertyList` 

35 Matching metadata to write in catalog. 

36 

37 Returns 

38 ------- 

39 catalog : `lsst.afw.table.BaseCatalog` 

40 Catalog containing matchlist entries. 

41 

42 Notes 

43 ----- 

44 This is intended for writing matches in a convenient way. 

45 Normally we write matches in a 'normalized' form: recording only the join 

46 table (reference ID, source ID) to minimise space (the reference and source 

47 catalogs should both be available separately, so the only extra information 

48 we need is how to join them). However, using that can be a pain, since it 

49 requires reading each catalog and doing the join. 

50 

51 This function generates a Catalog containing all the information in the 

52 matches. The reference catalog entries are in columns with 'ref' 

53 prepended, while the source catalog entries are in columns with 'src' 

54 prepended (including any alias mappings). The distance between the 

55 matches is in a column named "distance". 

56 

57 See Also 

58 -------- 

59 lsst.afw.table.packMatches 

60 """ 

61 # TODO: DM-16863 Current this link is removed due to the conversion of 

62 # afw.table not yet being complete and causing an error on build. 

63 # """ 

64 if len(matches) == 0: 

65 raise RuntimeError("No matches provided.") 

66 

67 refSchema = matches[0].first.getSchema() 

68 srcSchema = matches[0].second.getSchema() 

69 

70 refMapper, srcMapper = afwTable.SchemaMapper.join([refSchema, srcSchema], ["ref_", "src_"]) 

71 schema = refMapper.editOutputSchema() 

72 

73 schema = afwTable.catalogMatches.copyAliasMapWithPrefix(srcSchema, schema, prefix="src_") 

74 schema = afwTable.catalogMatches.copyAliasMapWithPrefix(refSchema, schema, prefix="ref_") 

75 

76 distKey = schema.addField("distance", type=float, doc="Distance between ref and src") 

77 

78 catalog = afwTable.BaseCatalog(schema) 

79 catalog.reserve(len(matches)) 

80 for mm in matches: 

81 row = catalog.addNew() 

82 row.assign(mm.first, refMapper) 

83 row.assign(mm.second, srcMapper) 

84 row.set(distKey, mm.distance) 

85 

86 if matchMeta is not None: 

87 catalog.getTable().setMetadata(matchMeta) 

88 

89 return catalog