Coverage for python/lsst/meas/astrom/match_probabilistic_task.py: 26%

Shortcuts on this page

r m x p   toggle line displays

j k   next/prev highlighted chunk

0   (zero) top of page

1   (one) first highlighted chunk

57 statements  

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 

22import lsst.afw.geom as afwGeom 

23import lsst.geom as geom 

24import lsst.pipe.base as pipeBase 

25from .matcher_probabilistic import MatchProbabilisticConfig, MatcherProbabilistic 

26 

27import logging 

28import numpy as np 

29import pandas as pd 

30from typing import Dict, Set, Tuple 

31 

32__all__ = ['MatchProbabilisticTask'] 

33 

34 

35class MatchProbabilisticTask(pipeBase.Task): 

36 """Run MatchProbabilistic on a reference and target catalog covering the same tract. 

37 """ 

38 ConfigClass = MatchProbabilisticConfig 

39 _DefaultName = "matchProbabilistic" 

40 

41 @property 

42 def columns_in_ref(self) -> Set[str]: 

43 return self.config.columns_in_ref() 

44 

45 @property 

46 def columns_in_target(self) -> Set[str]: 

47 return self.config.columns_in_target() 

48 

49 def match( 

50 self, 

51 catalog_ref: pd.DataFrame, 

52 catalog_target: pd.DataFrame, 

53 select_ref: np.array = None, 

54 select_target: np.array = None, 

55 wcs: afwGeom.SkyWcs = None, 

56 logger: logging.Logger = None, 

57 logging_n_rows: int = None, 

58 ) -> Tuple[pd.DataFrame, pd.DataFrame, Dict[int, str]]: 

59 """Match sources in a reference tract catalog with a target catalog. 

60 

61 Parameters 

62 ---------- 

63 catalog_ref : `pandas.DataFrame` 

64 A reference catalog to match objects/sources from. 

65 catalog_target : `pandas.DataFrame` 

66 A target catalog to match reference objects/sources to. 

67 select_ref : `numpy.array` 

68 A boolean array of the same length as `catalog_ref` selecting the sources that can be matched. 

69 select_target : `numpy.array` 

70 A boolean array of the same length as `catalog_target` selecting the sources that can be matched. 

71 wcs : `lsst.afw.image.SkyWcs` 

72 A coordinate system to convert catalog positions to sky coordinates. Only used if 

73 `self.config.coords_ref_to_convert` is set. 

74 logger : `logging.Logger` 

75 A Logger for logging. 

76 logging_n_rows : `int` 

77 Number of matches to make before outputting incremental log message. 

78 

79 Returns 

80 ------- 

81 catalog_out_ref : `pandas.DataFrame` 

82 Reference matched catalog with indices of target matches. 

83 catalog_out_target : `pandas.DataFrame` 

84 Reference matched catalog with indices of target matches. 

85 """ 

86 if logger is None: 

87 logger = self.log 

88 

89 config = self.config 

90 

91 if config.column_order is None: 

92 flux_tot = np.nansum(catalog_ref.loc[:, config.columns_ref_flux].values, axis=1) 

93 catalog_ref['flux_total'] = flux_tot 

94 if config.mag_brightest_ref != -np.inf or config.mag_faintest_ref != np.inf: 

95 mag_tot = -2.5 * np.log10(flux_tot) + config.mag_zeropoint_ref 

96 select_mag = (mag_tot >= config.mag_brightest_ref) & ( 

97 mag_tot <= config.mag_faintest_ref) 

98 else: 

99 select_mag = np.isfinite(flux_tot) 

100 if select_ref is None: 

101 select_ref = select_mag 

102 else: 

103 select_ref &= select_mag 

104 

105 if config.coords_ref_to_convert: 

106 ra_ref, dec_ref = [catalog_ref[column] for column in config.coords_ref_to_convert.keys()] 

107 factor = config.coords_ref_factor 

108 radec_true = [geom.SpherePoint(ra*factor, dec*factor, geom.degrees) 

109 for ra, dec in zip(ra_ref, dec_ref)] 

110 xy_true = wcs.skyToPixel(radec_true) 

111 

112 for idx_coord, column_out in enumerate(config.coords_ref_to_convert.values()): 

113 catalog_ref[column_out] = np.array([xy[idx_coord] for xy in xy_true]) 

114 

115 select_additional = (len(config.columns_target_select_true) 

116 + len(config.columns_target_select_false)) > 0 

117 if select_additional: 

118 if select_target is None: 

119 select_target = np.ones(len(catalog_target), dtype=bool) 

120 for column in config.columns_target_select_true: 

121 select_target &= catalog_target[column].values 

122 for column in config.columns_target_select_false: 

123 select_target &= ~catalog_target[column].values 

124 

125 logger.info('Beginning MatcherProbabilistic.match with %d/%d ref sources selected vs %d/%d target', 

126 np.sum(select_ref), len(select_ref), np.sum(select_target), len(select_target)) 

127 

128 catalog_out_ref, catalog_out_target, exceptions = self.matcher.match( 

129 catalog_ref, 

130 catalog_target, 

131 select_ref=select_ref, 

132 select_target=select_target, 

133 logger=logger, 

134 logging_n_rows=logging_n_rows, 

135 ) 

136 

137 return catalog_out_ref, catalog_out_target, exceptions 

138 

139 @pipeBase.timeMethod 

140 def run( 

141 self, 

142 catalog_ref: pd.DataFrame, 

143 catalog_target: pd.DataFrame, 

144 wcs: afwGeom.SkyWcs = None, 

145 **kwargs, 

146 ) -> pipeBase.Struct: 

147 """Match sources in a reference tract catalog with a target catalog. 

148 

149 Parameters 

150 ---------- 

151 catalog_ref : `pandas.DataFrame` 

152 A reference catalog to match objects/sources from. 

153 catalog_target : `pandas.DataFrame` 

154 A target catalog to match reference objects/sources to. 

155 wcs : `lsst.afw.image.SkyWcs` 

156 A coordinate system to convert catalog positions to sky coordinates. 

157 Only needed if `config.coords_ref_to_convert` is used to convert 

158 reference catalog sky coordinates to pixel positions. 

159 kwargs : Additional keyword arguments to pass to `match`. 

160 

161 Returns 

162 ------- 

163 retStruct : `lsst.pipe.base.Struct` 

164 A struct with output_ref and output_target attribute containing the 

165 output matched catalogs, as well as a dict 

166 """ 

167 catalog_ref, catalog_target, exceptions = self.match(catalog_ref, catalog_target, wcs=wcs, **kwargs) 

168 return pipeBase.Struct(cat_output_ref=catalog_ref, cat_output_target=catalog_target, 

169 exceptions=exceptions) 

170 

171 def __init__(self, **kwargs): 

172 super().__init__(**kwargs) 

173 self.matcher = MatcherProbabilistic(self.config)