Coverage for python/lsst/multiprofit/priors.py: 95%

1# This file is part of multiprofit. 

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__ = ["ShapePriorConfig", "get_hst_size_prior"] 

23 

24import numpy as np 

25 

26import lsst.gauss2d.fit as g2f 

27import lsst.pex.config as pexConfig 

28 

29from .transforms import transforms_ref 

30 

31 

32class ShapePriorConfig(pexConfig.Config): 

33 """Configuration for a shape prior.""" 

34 

35 prior_axrat_mean = pexConfig.Field[float]( 

36 default=0.7, 

37 doc="Prior mean for axis ratio (prior ignored if not >0)", 

38 ) 

39 prior_axrat_stddev = pexConfig.Field[float]( 

40 default=0, 

41 doc="Prior std. dev. on axis ratio", 

42 ) 

43 prior_size_mean = pexConfig.Field[float]( 

44 default=1, 

45 doc="Prior mean for size_major", 

46 ) 

47 prior_size_stddev = pexConfig.Field[float]( 

48 default=0, 

49 doc="Prior std. dev. on size_major (prior ignored if not >0)", 

50 ) 

51 

52 def make_shape_prior(self, ellipse: g2f.ParametricEllipse) -> g2f.ShapePrior | None: 

53 """Make a prior on ellipse (shape) parameters. 

54 

55 Parameters 

56 ---------- 

57 ellipse 

58 The ellipse to make a prior for. 

59 

60 Returns 

61 ------- 

62 prior 

63 The prior, or None if no positive stddev configured. 

64 """ 

65 use_prior_axrat = (self.prior_axrat_stddev > 0) and np.isfinite(self.prior_axrat_stddev) 

66 use_prior_size = (self.prior_size_stddev > 0) and np.isfinite(self.prior_size_stddev) 

67 

68 if use_prior_axrat or use_prior_size: 

69 prior_size = ( 

70 g2f.ParametricGaussian1D( 

71 g2f.MeanParameterD(self.prior_size_mean, transform=transforms_ref["log10"]), 

72 g2f.StdDevParameterD(self.prior_size_stddev), 

73 ) 

74 if use_prior_size 

75 else None 

76 ) 

77 prior_axrat = ( 

78 g2f.ParametricGaussian1D( 

79 g2f.MeanParameterD(self.prior_axrat_mean, transform=transforms_ref["logit_axrat_prior"]), 

80 g2f.StdDevParameterD(self.prior_axrat_stddev), 

81 ) 

82 if use_prior_axrat 

83 else None 

84 ) 

85 return g2f.ShapePrior(ellipse, prior_size, prior_axrat) 

86 return None 

87 

88 

89def get_hst_size_prior(mag_psf_i: float) -> float: 

90 """Return the mean and stddev for an HST-based size prior. 

91 

92 The size is major axis half-light radius. 

93 

94 Parameters 

95 ---------- 

96 mag_psf_i 

97 The i-band PSF magnitudes of the source(s). 

98 

99 Notes 

100 ----- 

101 Return values are log10 scaled in units of arcseconds. 

102 The input should be a PSF mag because other magnitudes - even Gaussian - 

103 can be unreliable for low S/N (non-)detections. 

104 """ 

105 return 0.75 * (19 - np.clip(mag_psf_i, 10, 30)) / 6.5, 0.2