Coverage for python/lsst/ip/isr/isrQa.py: 59%

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1# This file is part of ip_isr. 

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 

23__all__ = ["IsrQaFlatnessConfig", "IsrQaConfig", "makeThumbnail"] 

24 

25import lsst.afw.display.rgb as afwRGB 

26import lsst.afw.math as afwMath 

27import lsst.pex.config as pexConfig 

28 

29 

30class IsrQaFlatnessConfig(pexConfig.Config): 

31 meshX = pexConfig.Field( 

32 dtype=int, 

33 doc="Mesh size in X for flatness statistics", 

34 default=256, 

35 ) 

36 meshY = pexConfig.Field( 

37 dtype=int, 

38 doc="Mesh size in Y for flatness statistics", 

39 default=256, 

40 ) 

41 doClip = pexConfig.Field( 

42 dtype=bool, 

43 doc="Clip outliers for flatness statistics?", 

44 default=True, 

45 ) 

46 clipSigma = pexConfig.Field( 

47 dtype=float, 

48 doc="Number of sigma deviant a pixel must be to be clipped from flatness statistics.", 

49 default=3.0, 

50 ) 

51 nIter = pexConfig.Field( 

52 dtype=int, 

53 doc="Number of iterations used for outlier clipping in flatness statistics.", 

54 default=3, 

55 ) 

56 

57 

58class IsrQaConfig(pexConfig.Config): 

59 saveStats = pexConfig.Field( 

60 dtype=bool, 

61 doc="Calculate ISR statistics while processing?", 

62 default=True, 

63 ) 

64 

65 flatness = pexConfig.ConfigField( 

66 dtype=IsrQaFlatnessConfig, 

67 doc="Flatness statistics configuration.", 

68 ) 

69 

70 doWriteOss = pexConfig.Field( 

71 dtype=bool, 

72 doc="Write overscan subtracted image?", 

73 default=False, 

74 ) 

75 doThumbnailOss = pexConfig.Field( 

76 dtype=bool, 

77 doc="Write overscan subtracted thumbnail?", 

78 default=False, 

79 ) 

80 

81 doWriteFlattened = pexConfig.Field( 

82 dtype=bool, 

83 doc="Write image after flat-field correction?", 

84 default=False, 

85 ) 

86 doThumbnailFlattened = pexConfig.Field( 

87 dtype=bool, 

88 doc="Write thumbnail after flat-field correction?", 

89 default=False, 

90 ) 

91 

92 thumbnailBinning = pexConfig.Field( 

93 dtype=int, 

94 doc="Thumbnail binning factor.", 

95 default=4, 

96 ) 

97 thumbnailStdev = pexConfig.Field( 

98 dtype=float, 

99 doc="Number of sigma below the background to set the thumbnail minimum.", 

100 default=3.0, 

101 ) 

102 thumbnailRange = pexConfig.Field( 

103 dtype=float, 

104 doc="Total range in sigma for thumbnail mapping.", 

105 default=5.0, 

106 ) 

107 thumbnailQ = pexConfig.Field( 

108 dtype=float, 

109 doc="Softening parameter for thumbnail mapping.", 

110 default=20.0, 

111 ) 

112 thumbnailSatBorder = pexConfig.Field( 

113 dtype=int, 

114 doc="Width of border around saturated pixels in thumbnail.", 

115 default=2, 

116 ) 

117 

118 

119def makeThumbnail(exposure, isrQaConfig=None): 

120 """Create a snapshot thumbnail from input exposure. 

121 

122 The output thumbnail image is constructed based on the parameters 

123 in the configuration file. Currently, the asinh mapping is the 

124 only mapping method used. 

125 

126 Parameters 

127 ---------- 

128 exposure : `lsst.afw.image.Exposure` 

129 The exposure to be converted into a thumbnail. 

130 isrQaConfig : `Config` 

131 Configuration object containing all parameters to control the 

132 thumbnail generation. 

133 

134 Returns 

135 ------- 

136 rgbImage : `numpy.ndarray` 

137 Binned and scaled version of the exposure, converted to an 

138 integer array to allow it to be written as PNG. 

139 """ 

140 if isrQaConfig is not None: 

141 binning = isrQaConfig.thumbnailBinning 

142 binnedImage = afwMath.binImage(exposure.getMaskedImage(), binning, binning, afwMath.MEAN) 

143 

144 statsCtrl = afwMath.StatisticsControl() 

145 statsCtrl.setAndMask(binnedImage.getMask().getPlaneBitMask(["SAT", "BAD", "INTRP"])) 

146 stats = afwMath.makeStatistics(binnedImage, 

147 afwMath.MEDIAN | afwMath.STDEVCLIP | afwMath.MAX, statsCtrl) 

148 

149 low = stats.getValue(afwMath.MEDIAN) - isrQaConfig.thumbnailStdev*stats.getValue(afwMath.STDEVCLIP) 

150 

151 if isrQaConfig.thumbnailSatBorder: 

152 afwRGB.replaceSaturatedPixels(binnedImage, binnedImage, binnedImage, 

153 isrQaConfig.thumbnailSatBorder, stats.getValue(afwMath.MAX)) 

154 

155 asinhMap = afwRGB.AsinhMapping(low, isrQaConfig.thumbnailRange, Q=isrQaConfig.thumbnailQ) 

156 rgbImage = asinhMap.makeRgbImage(binnedImage) 

157 

158 return rgbImage