Coverage for python/lsst/faro/utils/coord_util.py: 27%

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1# This file is part of faro. 

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 numpy as np 

23 

24import lsst.geom as geom 

25 

26__all__ = ( 

27 "averageRaFromCat", 

28 "averageDecFromCat", 

29 "averageRaDecFromCat", 

30 "averageRaDec", 

31 "sphDist", 

32) 

33 

34 

35def averageRaFromCat(cat): 

36 """Compute the average right ascension from a catalog of measurements. 

37 This function is used as an aggregate function to extract just RA 

38 from a lsst.afw.table.MultiMatch final match catalog. 

39 The actual computation involves both RA and Dec. 

40 The intent is to use this for a set of measurements of the same source 

41 but that's neither enforced nor required. 

42 Parameters 

43 ---------- 

44 cat : collection 

45 Object with .get method for 'coord_ra', 'coord_dec' that returns radians. 

46 Returns 

47 ------- 

48 ra_mean : `float` 

49 Mean RA in radians. 

50 """ 

51 meanRa, meanDec = averageRaDecFromCat(cat) 

52 return meanRa 

53 

54 

55def averageDecFromCat(cat): 

56 """Compute the average declination from a catalog of measurements. 

57 This function is used as an aggregate function to extract just declination 

58 from a lsst.afw.table.MultiMatch final match catalog. 

59 The actual computation involves both RA and Dec. 

60 The intent is to use this for a set of measurements of the same source 

61 but that's neither enforced nor required. 

62 Parameters 

63 ---------- 

64 cat : collection 

65 Object with .get method for 'coord_ra', 'coord_dec' that returns radians. 

66 Returns 

67 ------- 

68 dec_mean : `float` 

69 Mean Dec in radians. 

70 """ 

71 meanRa, meanDec = averageRaDecFromCat(cat) 

72 return meanDec 

73 

74 

75def averageRaDecFromCat(cat): 

76 """Calculate the average right ascension and declination from a catalog. 

77 Convenience wrapper around averageRaDec 

78 Parameters 

79 ---------- 

80 cat : collection 

81 Object with .get method for 'coord_ra', 'coord_dec' that returns radians. 

82 Returns 

83 ------- 

84 ra_mean : `float` 

85 Mean RA in radians. 

86 dec_mean : `float` 

87 Mean Dec in radians. 

88 """ 

89 return averageRaDec(cat.get("coord_ra"), cat.get("coord_dec")) 

90 

91 

92def averageRaDec(ra, dec): 

93 """Calculate average RA, Dec from input lists using spherical geometry. 

94 Parameters 

95 ---------- 

96 ra : `list` [`float`] 

97 RA in [radians] 

98 dec : `list` [`float`] 

99 Dec in [radians] 

100 Returns 

101 ------- 

102 float, float 

103 meanRa, meanDec -- Tuple of average RA, Dec [radians] 

104 """ 

105 assert len(ra) == len(dec) 

106 

107 angleRa = [geom.Angle(r, geom.radians) for r in ra] 

108 angleDec = [geom.Angle(d, geom.radians) for d in dec] 

109 coords = [ 

110 geom.SpherePoint(ar, ad, geom.radians) for (ar, ad) in zip(angleRa, angleDec) 

111 ] 

112 

113 meanRa, meanDec = geom.averageSpherePoint(coords) 

114 

115 return meanRa.asRadians(), meanDec.asRadians() 

116 

117 

118def sphDist(ra_mean, dec_mean, ra, dec): 

119 """Calculate distance on the surface of a unit sphere. 

120 Parameters 

121 ---------- 

122 ra_mean : `float` 

123 Mean RA in radians. 

124 dec_mean : `float` 

125 Mean Dec in radians. 

126 ra : `numpy.array` [`float`] 

127 Array of RA in radians. 

128 dec : `numpy.array` [`float`] 

129 Array of Dec in radians. 

130 Notes 

131 ----- 

132 Uses the Haversine formula to preserve accuracy at small angles. 

133 Law of cosines approach doesn't work well for the typically very small 

134 differences that we're looking at here. 

135 """ 

136 # Haversine 

137 dra = ra - ra_mean 

138 ddec = dec - dec_mean 

139 a = np.square(np.sin(ddec / 2)) + np.cos(dec_mean) * np.cos(dec) * np.square( 

140 np.sin(dra / 2) 

141 ) 

142 dist = 2 * np.arcsin(np.sqrt(a)) 

143 

144 # This is what the law of cosines would look like 

145 # dist = np.arccos(np.sin(dec1)*np.sin(dec2) + np.cos(dec1)*np.cos(dec2)*np.cos(ra1 - ra2)) 

146 

147 # This will also work, but must run separately for each element 

148 # whereas the numpy version will run on either scalars or arrays: 

149 # sp1 = geom.SpherePoint(ra1, dec1, geom.radians) 

150 # sp2 = geom.SpherePoint(ra2, dec2, geom.radians) 

151 # return sp1.separation(sp2).asRadians() 

152 

153 return dist