Coverage for python/lsst/source/injection/inject_coadd.py: 44%

1# This file is part of source_injection. 

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 

22from __future__ import annotations 

23 

24__all__ = ["CoaddInjectConnections", "CoaddInjectConfig", "CoaddInjectTask"] 

25 

26import dataclasses 

27from typing import cast 

28 

29from lsst.pex.config import Field 

30from lsst.pipe.base.connectionTypes import Input, Output 

31 

32from .inject_base import BaseInjectConfig, BaseInjectConnections, BaseInjectTask 

33 

34 

35class CoaddInjectConnections( 

36 BaseInjectConnections, 

37 dimensions=("skymap", "tract", "patch", "band"), 

38 defaultTemplates={ 

39 "coadd_name": "deep", 

40 }, 

41): 

42 """Coadd-level connections for source injection tasks.""" 

43 

44 input_exposure = Input( 

45 doc="Exposure to inject synthetic sources into.", 

46 name="{coadd_name}_coadd_predetection", 

47 storageClass="ExposureF", 

48 dimensions=("skymap", "tract", "patch", "band"), 

49 ) 

50 output_exposure = Output( 

51 doc="Injected Exposure.", 

52 name="{injected_prefix}{coadd_name}_coadd_predetection", 

53 storageClass="ExposureF", 

54 dimensions=("skymap", "tract", "patch", "band"), 

55 ) 

56 output_catalog = Output( 

57 doc="Catalog of injected sources.", 

58 name="{injected_prefix}{coadd_name}_coadd_predetection_catalog", 

59 storageClass="ArrowAstropy", 

60 dimensions=("skymap", "tract", "patch", "band"), 

61 ) 

62 

63 def __init__(self, *, config: CoaddInjectConfig | None = None): 

64 super().__init__(config=config) 

65 

66 if not self.config: 

67 return 

68 

69 if self.config.use_cell_coadds: 

70 self.input_exposure = dataclasses.replace(self.input_exposure, storageClass="CellCoadd") 

71 self.output_exposure = dataclasses.replace(self.output_exposure, storageClass="CellCoadd") 

72 

73 

74class CoaddInjectConfig( # type: ignore [call-arg] 

75 BaseInjectConfig, 

76 pipelineConnections=CoaddInjectConnections, 

77): 

78 """Coadd-level configuration for source injection tasks.""" 

79 

80 use_cell_coadds = Field(dtype=bool, default=False, doc="Whether to use cell coadds?") 

81 

82 

83class CoaddInjectTask(BaseInjectTask): 

84 """Coadd-level class for injecting sources into images.""" 

85 

86 _DefaultName = "coaddInjectTask" 

87 ConfigClass = CoaddInjectConfig 

88 

89 def runQuantum(self, butler_quantum_context, input_refs, output_refs): 

90 inputs = butler_quantum_context.get(input_refs) 

91 

92 config = cast(self.ConfigClass, self.config) 

93 exposure = inputs["input_exposure"] 

94 if config.use_cell_coadds: 

95 exposure.apply_background(None) 

96 else: 

97 inputs["psf"] = exposure.getPsf() 

98 inputs["photo_calib"] = exposure.getPhotoCalib() 

99 inputs["wcs"] = exposure.getWcs() 

100 

101 input_keys = ["injection_catalogs", "input_exposure", "sky_map", "psf", "photo_calib", "wcs"] 

102 outputs = self.run(**{key: value for (key, value) in inputs.items() if key in input_keys}) 

103 butler_quantum_context.put(outputs, output_refs)