Coverage for python/lsst/meas/astrom/match_probabilistic_task.py: 37%

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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 

22import lsst.afw.geom as afwGeom 

23import lsst.geom as geom 

24import lsst.pipe.base as pipeBase 

25import lsst.utils as utils 

26from .matcher_probabilistic import MatchProbabilisticConfig, MatcherProbabilistic 

27 

28import logging 

29import numpy as np 

30import pandas as pd 

31from typing import Dict, List, Optional, Set, Tuple 

32 

33__all__ = ['MatchProbabilisticTask', 'radec_to_xy'] 

34 

35 

36def radec_to_xy(ra_vec, dec_vec, factor, wcs: afwGeom.SkyWcs): 

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

38 for ra, dec in zip(ra_vec, dec_vec)] 

39 return wcs.skyToPixel(radec_true) 

40 

41 

42class MatchProbabilisticTask(pipeBase.Task): 

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

44 """ 

45 ConfigClass = MatchProbabilisticConfig 

46 _DefaultName = "matchProbabilistic" 

47 

48 @staticmethod 

49 def _apply_select_bool( 

50 catalog: pd.DataFrame, 

51 columns_true: List[str], 

52 columns_false: List[str], 

53 selection: Optional[np.array], 

54 ) -> np.array: 

55 """ Apply additional boolean selection columns. 

56 

57 catalog : `pandas.DataFrame` 

58 The catalog to select from. 

59 columns_true : `list` [`str`] 

60 Columns that must be True for selection. 

61 columns_false : `list` [`str`] 

62 Columns that must be False for selection. 

63 selection : `numpy.array` 

64 A prior selection array. Default all true. 

65 

66 Returns 

67 ------- 

68 selection : `numpy.array` 

69 The final selection array. 

70 

71 """ 

72 select_additional = (len(columns_true) + len(columns_false)) > 0 

73 if select_additional: 

74 if selection is None: 

75 selection = np.ones(len(catalog), dtype=bool) 

76 for column in columns_true: 

77 selection &= catalog[column].values 

78 for column in columns_false: 

79 selection &= ~catalog[column].values 

80 return selection 

81 

82 @property 

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

84 return self.config.columns_in_ref 

85 

86 @property 

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

88 return self.config.columns_in_target 

89 

90 def match( 

91 self, 

92 catalog_ref: pd.DataFrame, 

93 catalog_target: pd.DataFrame, 

94 select_ref: np.array = None, 

95 select_target: np.array = None, 

96 wcs: afwGeom.SkyWcs = None, 

97 logger: logging.Logger = None, 

98 logging_n_rows: int = None, 

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

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

101 

102 Parameters 

103 ---------- 

104 catalog_ref : `pandas.DataFrame` 

105 A reference catalog to match objects/sources from. 

106 catalog_target : `pandas.DataFrame` 

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

108 select_ref : `numpy.array` 

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

110 select_target : `numpy.array` 

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

112 wcs : `lsst.afw.image.SkyWcs` 

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

114 `self.config.coords_ref_to_convert` is set. 

115 logger : `logging.Logger` 

116 A Logger for logging. 

117 logging_n_rows : `int` 

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

119 

120 Returns 

121 ------- 

122 catalog_out_ref : `pandas.DataFrame` 

123 Reference matched catalog with indices of target matches. 

124 catalog_out_target : `pandas.DataFrame` 

125 Reference matched catalog with indices of target matches. 

126 """ 

127 if logger is None: 

128 logger = self.log 

129 

130 config = self.config 

131 

132 if config.column_ref_order is None: 

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

134 catalog_ref['flux_total'] = flux_tot 

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

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

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

138 mag_tot <= config.mag_faintest_ref) 

139 else: 

140 select_mag = np.isfinite(flux_tot) 

141 if select_ref is None: 

142 select_ref = select_mag 

143 else: 

144 select_ref &= select_mag 

145 

146 select_ref = self._apply_select_bool( 

147 catalog=catalog_ref, 

148 columns_true=config.columns_ref_select_true, 

149 columns_false=config.columns_ref_select_false, 

150 selection=select_ref 

151 ) 

152 select_target = self._apply_select_bool( 

153 catalog=catalog_target, 

154 columns_true=config.columns_target_select_true, 

155 columns_false=config.columns_target_select_false, 

156 selection=select_target 

157 ) 

158 

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

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

161 

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

163 catalog_ref, 

164 catalog_target, 

165 select_ref=select_ref, 

166 select_target=select_target, 

167 logger=logger, 

168 logging_n_rows=logging_n_rows, 

169 wcs=wcs, 

170 radec_to_xy_func=radec_to_xy, 

171 ) 

172 

173 return catalog_out_ref, catalog_out_target, exceptions 

174 

175 @utils.timer.timeMethod 

176 def run( 

177 self, 

178 catalog_ref: pd.DataFrame, 

179 catalog_target: pd.DataFrame, 

180 wcs: afwGeom.SkyWcs = None, 

181 **kwargs, 

182 ) -> pipeBase.Struct: 

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

184 

185 Parameters 

186 ---------- 

187 catalog_ref : `pandas.DataFrame` 

188 A reference catalog to match objects/sources from. 

189 catalog_target : `pandas.DataFrame` 

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

191 wcs : `lsst.afw.image.SkyWcs` 

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

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

194 reference catalog sky coordinates to pixel positions. 

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

196 

197 Returns 

198 ------- 

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

200 A struct with output_ref and output_target attribute containing the 

201 output matched catalogs, as well as a dict 

202 """ 

203 catalog_ref.reset_index(inplace=True) 

204 catalog_target.reset_index(inplace=True) 

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

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

207 exceptions=exceptions) 

208 

209 def __init__(self, **kwargs): 

210 super().__init__(**kwargs) 

211 self.matcher = MatcherProbabilistic(self.config)