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1# Copyright (C) 2017 HSC Software Team 

2# Copyright (C) 2017 Sogo Mineo 

3# 

4# This program is free software: you can redistribute it and/or modify 

5# it under the terms of the GNU General Public License as published by 

6# the Free Software Foundation, either version 3 of the License, or 

7# (at your option) any later version. 

8# 

9# This program is distributed in the hope that it will be useful, 

10# but WITHOUT ANY WARRANTY; without even the implied warranty of 

11# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

12# GNU General Public License for more details. 

13# 

14# You should have received a copy of the GNU General Public License 

15# along with this program. If not, see <http://www.gnu.org/licenses/>. 

16 

17__all__ = ["SubaruStrayLightTask"] 

18 

19import datetime 

20from typing import Optional 

21 

22import numpy 

23from astropy.io import fits 

24import scipy.interpolate 

25 

26from lsst.geom import Angle, degrees 

27from lsst.ip.isr.straylight import StrayLightConfig, StrayLightTask, StrayLightData 

28 

29from . import waveletCompression 

30from .rotatorAngle import inrStartEnd 

31 

32 

33BAD_THRESHOLD = 500 # Threshold for identifying bad pixels in the reconstructed dark image 

34 

35 

36# TODO DM-16805: This doesn't match the rest of the obs_subaru/ISR code. 

37class SubaruStrayLightTask(StrayLightTask): 

38 """Remove stray light in the y-band 

39 

40 LEDs in an encoder in HSC are producing stray light on the detectors, 

41 producing the "Eye of Y-band" feature. It can be removed by 

42 subtracting open-shutter darks. However, because the pattern of stray 

43 light varies with rotator angle, many dark exposures are required. 

44 To reduce the data volume for the darks, the images have been 

45 compressed using wavelets. The code used to construct these is at: 

46 

47 https://hsc-gitlab.mtk.nao.ac.jp/sogo.mineo/ybackground/ 

48 

49 This Task retrieves the appropriate dark, uncompresses it and 

50 uses it to remove the stray light from an exposure. 

51 """ 

52 ConfigClass = StrayLightConfig 

53 

54 def readIsrData(self, dataRef, rawExposure): 

55 # Docstring inherited from StrayLightTask.runIsrTask. 

56 # Note that this is run only in Gen2; in Gen3 we will rely on having 

57 # a proper butler-recognized dataset type with the right validity 

58 # ranges (though this has not yet been implemented). 

59 if not self.check(rawExposure): 

60 return None 

61 

62 return SubaruStrayLightData(dataRef.get("yBackground_filename")[0]) 

63 

64 def check(self, exposure): 

65 # Docstring inherited from StrayLightTask.check. 

66 detId = exposure.getDetector().getId() 

67 if not self.checkFilter(exposure): 

68 # No correction to be made 

69 return False 

70 if detId in range(104, 112): 

71 # No correction data: assume it's zero 

72 return False 

73 if exposure.getInfo().getVisitInfo().getDate().toPython() >= datetime.datetime(2018, 1, 1): 

74 # LEDs causing the stray light have been covered up. 

75 # We believe there is no remaining stray light. 

76 return False 

77 

78 return True 

79 

80 def run(self, exposure, strayLightData): 

81 """Subtract the y-band stray light 

82 

83 This relies on knowing the instrument rotator angle during the 

84 exposure. The FITS headers provide only the instrument rotator 

85 angle at the start of the exposure (INR_STR), but better 

86 stray light removal is obtained when we calculate the start and 

87 end instrument rotator angles ourselves (config parameter 

88 ``doRotatorAngleCorrection=True``). 

89 

90 Parameters 

91 ---------- 

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

93 Exposure to correct. 

94 strayLightData : `SubaruStrayLightData` 

95 An opaque object that contains any calibration data used to 

96 correct for stray light. 

97 """ 

98 if not self.check(exposure): 

99 return None 

100 

101 if strayLightData is None: 

102 raise RuntimeError("No strayLightData supplied for correction.") 

103 

104 exposureMetadata = exposure.getMetadata() 

105 detId = exposure.getDetector().getId() 

106 if self.config.doRotatorAngleCorrection: 

107 angleStart, angleEnd = inrStartEnd(exposure.getInfo().getVisitInfo()) 

108 self.log.debug( 

109 "(INR-STR, INR-END) = ({:g}, {:g}) (FITS header says ({:g}, {:g})).".format( 

110 angleStart, angleEnd, 

111 exposureMetadata.getDouble('INR-STR'), exposureMetadata.getDouble('INR-END')) 

112 ) 

113 else: 

114 angleStart = exposureMetadata.getDouble('INR-STR') 

115 angleEnd = None 

116 

117 self.log.info("Correcting y-band background.") 

118 

119 model = strayLightData.evaluate(angleStart*degrees, 

120 None if angleStart == angleEnd else angleEnd*degrees) 

121 

122 # Some regions don't have useful model values because the amplifier is dead when the darks were taken 

123 # 

124 badAmps = {9: [0, 1, 2, 3], 33: [0, 1], 43: [0]} # Known bad amplifiers in the data: {ccdId: [ampId]} 

125 if detId in badAmps: 

126 isBad = numpy.zeros_like(model, dtype=bool) 

127 for ii in badAmps[detId]: 

128 amp = exposure.getDetector()[ii] 

129 box = amp.getBBox() 

130 isBad[box.getBeginY():box.getEndY(), box.getBeginX():box.getEndX()] = True 

131 mask = exposure.getMaskedImage().getMask() 

132 if numpy.all(isBad): 

133 model[:] = 0.0 

134 else: 

135 model[isBad] = numpy.median(model[~isBad]) 

136 mask.array[isBad] |= mask.getPlaneBitMask("SUSPECT") 

137 

138 model *= exposure.getInfo().getVisitInfo().getExposureTime() 

139 exposure.image.array -= model 

140 

141 

142class SubaruStrayLightData(StrayLightData): 

143 """Lazy-load object that reads and integrates the wavelet-compressed 

144 HSC y-band stray-light model. 

145 

146 Parameters 

147 ---------- 

148 filename : `str` 

149 Full path to a FITS files containing the stray-light model. 

150 """ 

151 

152 def __init__(self, filename): 

153 self._filename = filename 

154 

155 def evaluate(self, angle_start: Angle, angle_end: Optional[Angle] = None): 

156 """Get y-band background image array for a range of angles. 

157 

158 It is hypothesized that the instrument rotator rotates at a constant 

159 angular velocity. This is not strictly true, but should be a 

160 sufficient approximation for the relatively short exposure times 

161 typical for HSC. 

162 

163 Parameters 

164 ---------- 

165 angle_start : `float` 

166 Instrument rotation angle in degrees at the start of the exposure. 

167 angle_end : `float`, optional 

168 Instrument rotation angle in degrees at the end of the exposure. 

169 If not provided, the returned array will reflect a snapshot at 

170 `angle_start`. 

171 

172 Returns 

173 ------- 

174 ccd_img : `numpy.ndarray` 

175 Background data for this exposure. 

176 """ 

177 hdulist = fits.open(self._filename) 

178 header = hdulist[0].header 

179 

180 # full-size ccd height & channel width 

181 ccd_h, ch_w = header["F_NAXIS2"], header["F_NAXIS1"] 

182 # saved data is compressed to 1/2**scale_level of the original size 

183 image_scale_level = header["WTLEVEL2"], header["WTLEVEL1"] 

184 angle_scale_level = header["WTLEVEL3"] 

185 

186 ccd_w = ch_w * len(hdulist) 

187 ccd_img = numpy.empty(shape=(ccd_h, ccd_w), dtype=numpy.float32) 

188 

189 for ch, hdu in enumerate(hdulist): 

190 volume = _upscale_volume(hdu.data, angle_scale_level) 

191 

192 if angle_end is None: 

193 img = volume(angle_start.asDegrees()) 

194 else: 

195 img = (volume.integrate(angle_start.asDegrees(), angle_end.asDegrees()) * 

196 (1.0 / (angle_end.asDegrees() - angle_start.asDegrees()))) 

197 

198 ccd_img[:, ch_w*ch:ch_w*(ch+1)] = _upscale_image(img, (ccd_h, ch_w), image_scale_level) 

199 

200 # Some regions don't have useful values because the amplifier is dead when the darks were taken 

201 # is_bad = ccd_img > BAD_THRESHOLD 

202 # ccd_img[is_bad] = numpy.median(ccd_img[~is_bad]) 

203 

204 return ccd_img 

205 

206 

207def _upscale_image(img, target_shape, level): 

208 """ 

209 Upscale the given image to `target_shape` . 

210 

211 @param img (numpy.array[][]) 

212 Compressed image. `img.shape` must agree 

213 with waveletCompression.scaled_size(target_shape, level) 

214 @param target_shape ((int, int)) 

215 The shape of upscaled image, which is to be returned. 

216 @param level (int or tuple of int) 

217 Level of multiresolution analysis (or synthesis) 

218 

219 @return (numpy.array[][]) 

220 """ 

221 h, w = waveletCompression.scaled_size(target_shape, level) 

222 

223 large_img = numpy.zeros(shape=target_shape, dtype=float) 

224 large_img[:h, :w] = img 

225 

226 return waveletCompression.icdf_9_7(large_img, level) 

227 

228 

229def _upscale_volume(volume, level): 

230 """ 

231 Upscale the given volume (= sequence of images) along the 0-th axis, 

232 and return an instance of a interpolation object that interpolates 

233 the 0-th axis. The 0-th axis is the instrument rotation. 

234 

235 @param volume (numpy.array[][][]) 

236 Sequence of images. 

237 @param level (int) 

238 Level of multiresolution analysis along the 0-th axis. 

239 

240 @return (scipy.interpolate.CubicSpline) 

241 You get a slice of the volume at a specific angle (in degrees) 

242 by calling the returned value as `ret_value(angle)` . 

243 """ 

244 angles = 720 

245 _, h, w = volume.shape 

246 

247 large_volume = numpy.zeros(shape=(angles+1, h, w), dtype=float) 

248 

249 layers = waveletCompression.scaled_size(angles, level) 

250 large_volume[:layers] = volume 

251 

252 large_volume[:-1] = waveletCompression.periodic_icdf_9_7_1d(large_volume[:-1], level, axis=0) 

253 large_volume[-1] = large_volume[0] 

254 

255 x = numpy.arange(angles+1) / 2.0 

256 return scipy.interpolate.CubicSpline(x, large_volume, axis=0, bc_type="periodic")