Coverage for tests/test_deferredCharge.py: 24%

2# LSST Data Management System

6# This product includes software developed by the

7# LSST Project (http://www.lsst.org/).

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#

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20# the GNU General Public License along with this program. If not,

21# see <https://www.lsstcorp.org/LegalNotices/>.

22#

23"""Test cases for lsst.cp.pipe.deferredCharge."""

25import unittest

26import numpy

28import lsst.utils

29import lsst.utils.tests

31import lsst.cp.pipe as cpPipe

32from lsst.ip.isr import IsrMock, PhotonTransferCurveDataset

35class CpCtiSolveTaskTestCase(lsst.utils.tests.TestCase):

36 """A test case for the deferred charge/CTI solve task."""

38 def setUp(self):

39 self.camera = IsrMock().getCamera()

41 serialOscanMeansA = [

42 7.18039751e-01, 4.56550479e-01, 4.14261669e-01, 2.88099229e-01, -2.34310962e-02,

43 -4.59854975e-02, -1.14491098e-02, 5.19846082e-02, 2.05635265e-01, 1.25147207e-02,

44 9.00449380e-02, -2.39106059e-01, -1.52413145e-01, 4.63459678e-02, 1.85195580e-01,

45 -1.58051759e-01, -8.76842241e-04, -5.09192124e-02, 2.58496821e-01, 2.54267782e-01,

46 -1.37611866e-01, 3.35322201e-01, 1.04846083e-01, -2.16551736e-01, -8.82746354e-02,

47 -1.00256450e-01, 2.73297966e-01, -4.52805981e-02, 3.40960979e-01, 7.80628920e-02,

48 -2.90697180e-02, -6.99492991e-02, -1.06599867e-01, 6.89002723e-02, 1.46290688e-02,

49 1.19647197e-01, -1.54527843e-01, 9.35689881e-02, -1.06599934e-01, -2.13166289e-02,

50 9.35688764e-02, -1.19286761e-01, 1.18098985e-02, -3.69616691e-03, -6.14914447e-02,

51 -5.81059000e-03, 9.42736641e-02, 3.92978266e-02, -1.55937240e-01, 3.76202404e-01,

52 -1.13648064e-01, 1.71803936e-01, 6.17138995e-03, 8.22918862e-02, -2.84214199e-01,

53 -2.99097435e-03, -1.31973490e-01, -2.84214795e-01, -2.99140741e-03, -3.76546055e-01,

54 5.97376414e-02, -1.91883057e-01, -1.34087920e-01, -3.23684871e-01,

55 ]

56 serialOscanMeansB = [

57 1.50365152e+01, 4.43178511e+00, 2.66550946e+00, 1.67382801e+00, 1.10997069e+00,

58 8.89361799e-01, 4.66469795e-01, 6.10956728e-01, 6.67343795e-01, 5.22854805e-01,

59 -1.15006611e-01, 2.67710119e-01, 2.05686077e-01, 1.84541523e-01, 8.65717679e-02,

60 5.51738311e-03, 2.35288814e-01, 3.45944524e-01, 7.81139359e-02, 1.52119964e-01,

61 2.02162191e-01, 3.44150960e-02, -2.86277920e-01, 1.43662184e-01, 3.21276844e-01,

62 -6.21452965e-02, 8.58670697e-02, -1.63320359e-02, -1.07958235e-01, -1.60820082e-01,

63 -2.19705645e-02, -1.55181482e-01, -2.39055425e-01, -2.75705636e-01, 6.33126274e-02,

64 -5.50971478e-02, -2.42579415e-01, -9.87957790e-02, 1.08421087e-01, -1.12892322e-01,

65 1.89090632e-02, -1.53086300e-03, -2.18615308e-01, -2.19320312e-01, 9.22102109e-02,

66 -4.87535410e-02, -1.81964979e-01, -4.17055413e-02, -4.24422681e-01, -1.96061105e-01,

67 -1.35127297e-02, -1.77031055e-01, -2.30597332e-01, -4.01868790e-01, -4.18784261e-01,

68 -3.75085384e-01, -3.49007100e-01, -1.77735761e-01, -7.41272718e-02, -1.92537069e-01,

69 2.46565759e-01, -3.44777972e-01, -2.85573214e-01, -2.34121397e-01,

70 ]

71 serialOscanMeansC = [

72 0.212578110, 0.107817403, -0.122200218, -0.0089812368, -0.067990060, 0.040077099,

73 -0.021402006, 0.090923088, -0.099587158, 0.274797124, -0.016930788, 0.045007070,

74 -0.00379911056, -0.16088248, 0.055911896, 0.0601755001, -0.046872945, 0.210018355,

75 0.081641635, -0.046147249, -0.0059020276, 0.108368757, -0.033966731, -0.0058644798,

76 -0.075746922, -0.203826510, 0.12620401, -0.0156685544, -0.09631182, 0.089754454,

77 0.03789926, 0.0304515115, -0.082173715, -0.061332140, -0.24894494, -0.155137551,

78 -0.073825312, 0.24538413, -0.069597074, 0.192338801, -0.0539746876, -0.184556000,

79 -0.173069382, -0.209975778, 0.086679191, 0.016299034, -0.0094125706, -0.100099911,

80 0.061981365, 0.086250364, 0.209128404, -0.0067993622, 0.171072270, -0.29266333,

81 0.075172274, -0.29375612, -0.13377650, 0.0125964781, -0.124991264, 0.226516831,

82 0.128244484, -0.05019844, -0.149249925, -0.1557398,

83 ]

84 serialOscanMeansD = [

85 4.0867248, 1.43194193, 0.95319573, 0.43219185, 0.53112239, 0.28648, 0.323903486,

86 0.27622156, 0.26031138, 0.144442975, 0.0149878587, 0.062969929, 0.018541051,

87 -0.237687056, 0.22804558, 0.0600504708, 0.140250022, -0.137477808, 0.119911710,

88 0.03770870, -0.20021377, 0.187175400, 0.0168790129, -0.110724371, 0.099311580,

89 0.0079969534, -0.157593577, -0.178876067, -0.214948580, -0.11354382, 0.148154530,

90 -0.056012520, 0.11851939, 0.067902033, 0.18970736, -0.181487703, -0.0101017127,

91 0.100998570, -0.0309096733, -0.034450136, -0.066357072, -0.058662959, 0.146185921,

92 -0.218474021, -0.173691633, 0.055349625, -0.178158524, -0.012917378, -0.166576555,

93 -0.063862754, 0.113169933, -0.33518338, -0.074239500, 0.22262230, -0.066653975,

94 -0.200271016, -0.013275277, 0.100596499, -0.092528954, 0.0339541714, 0.113119135,

95 -0.150720824, 0.038237873, 0.17603852613429813,

96 ]

97 parallelOscanMeans = [

98 7.18039751e-01, 4.56550479e-01, 4.14261669e-01, 2.88099229e-01, -2.34310962e-02,

99 -4.59854975e-02, -1.14491098e-02, 5.19846082e-02, 2.05635265e-01, 1.25147207e-02,

100 ]

101

102 self.inputMeasurements = [

103 {'CTI': {'C:0,0': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

104 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

105 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

106 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

107 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

108 'INPUT_GAIN': 1.5},

109 'C:0,1': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

110 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

111 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

112 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

113 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

114 'INPUT_GAIN': 1.5},

115 'C:0,2': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

116 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

117 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

118 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

119 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

120 'INPUT_GAIN': 1.5},

121 'C:0,3': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

122 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

123 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

124 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

125 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

126 'INPUT_GAIN': 1.5},

127 'C:1,0': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

128 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

129 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

130 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

131 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

132 'INPUT_GAIN': 1.5},

133 'C:1,1': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

134 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

135 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

136 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

137 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

138 'INPUT_GAIN': 1.5},

139 'C:1,2': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

140 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

141 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

142 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

143 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

144 'INPUT_GAIN': 1.5},

145 'C:1,3': {'FIRST_COLUMN_MEAN': 117.810165, 'LAST_COLUMN_MEAN': 1.09791130e+02,

146 'IMAGE_MEAN': 117.810165, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansA,

147 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

148 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

149 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

150 'INPUT_GAIN': 1.5}}},

151

152 {'CTI': {'C:0,0': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

153 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

154 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

155 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

156 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

157 'INPUT_GAIN': 1.5},

158 'C:0,1': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

159 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

160 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

161 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

162 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

163 'INPUT_GAIN': 1.5},

164 'C:0,2': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

165 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

166 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

167 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

168 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

169 'INPUT_GAIN': 1.5},

170 'C:0,3': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

171 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

172 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

173 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

174 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

175 'INPUT_GAIN': 1.5},

176 'C:1,0': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

177 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

178 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

179 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

180 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

181 'INPUT_GAIN': 1.5},

182 'C:1,1': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

183 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

184 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

185 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

186 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

187 'INPUT_GAIN': 1.5},

188 'C:1,2': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

189 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

190 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

191 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

192 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

193 'INPUT_GAIN': 1.5},

194 'C:1,3': {'FIRST_COLUMN_MEAN': 36562.082, 'LAST_COLUMN_MEAN': 3.45901172e+04,

195 'IMAGE_MEAN': 36562.082, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansB,

196 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

197 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

198 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

199 'INPUT_GAIN': 1.5}}},

200

201 {'CTI': {'C:0,0': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

202 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

203 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

204 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

205 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

206 'INPUT_GAIN': 1.5},

207 'C:0,1': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

208 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

209 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

210 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

211 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

212 'INPUT_GAIN': 1.5},

213 'C:0,2': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

214 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

215 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

216 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

217 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

218 'INPUT_GAIN': 1.5},

219 'C:0,3': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

220 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

221 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

222 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

223 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

224 'INPUT_GAIN': 1.5},

225 'C:1,0': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

226 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

227 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

228 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

229 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

230 'INPUT_GAIN': 1.5},

231 'C:1,1': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

232 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

233 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

234 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

235 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

236 'INPUT_GAIN': 1.5},

237 'C:1,2': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

238 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

239 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

240 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

241 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

242 'INPUT_GAIN': 1.5},

243 'C:1,3': {'FIRST_COLUMN_MEAN': 994.811, 'LAST_COLUMN_MEAN': 936.415,

244 'IMAGE_MEAN': 994.811, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansC,

245 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

246 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

247 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

248 'INPUT_GAIN': 1.5}}},

249

250 {'CTI': {'C:0,0': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

251 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

252 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

253 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

254 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

255 'INPUT_GAIN': 1.5},

256 'C:0,1': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

257 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

258 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

259 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

260 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

261 'INPUT_GAIN': 1.5},

262 'C:0,2': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

263 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

264 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

265 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

266 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

267 'INPUT_GAIN': 1.5},

268 'C:0,3': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

269 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

270 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

271 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

272 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

273 'INPUT_GAIN': 1.5},

274 'C:1,0': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

275 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

276 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

277 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

278 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

279 'INPUT_GAIN': 1.5},

280 'C:1,1': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

281 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

282 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

283 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

284 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

285 'INPUT_GAIN': 1.5},

286 'C:1,2': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

287 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

288 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

289 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

290 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

291 'INPUT_GAIN': 1.5},

292 'C:1,3': {'FIRST_COLUMN_MEAN': 12215.778, 'LAST_COLUMN_MEAN': 11536.875,

293 'IMAGE_MEAN': 12215.778, 'SERIAL_OVERSCAN_VALUES': serialOscanMeansD,

294 'SERIAL_OVERSCAN_COLUMNS': [x for x in range(0, 64)],

295 'PARALLEL_OVERSCAN_VALUES': parallelOscanMeans,

296 'PARALLEL_OVERSCAN_ROWS': [x for x in range(0, 10)],

297 'INPUT_GAIN': 1.5}}}]

298 self.inputDims = [{'detector': 20, 'instrument': 'IsrMock', 'exposure': 2019101200433},

299 {'detector': 20, 'instrument': 'IsrMock', 'exposure': 2019101300154},

300 {'detector': 20, 'instrument': 'IsrMock', 'exposure': 2019101300004},

301 {'detector': 20, 'instrument': 'IsrMock', 'exposure': 2019101200333}]

302

303 self.task = cpPipe.CpCtiSolveTask()

304

305 self.ptc = PhotonTransferCurveDataset()

306 self.ptc.updateMetadata(camera=self.camera, detector=self.camera[20])

307 self.sequencerMetadata = {

308 "SEQNAME": "a_sequencer",

309 "SEQFILE": "a_sequencer_file",

310 "SEQCKSUM": "deadbeef",

311 }

312 self.ptc.updateMetadata(**self.sequencerMetadata, setCalibInfo=True)

313

314 def test_task(self):

315 """A test for the main CpCtiSolveTask.

316

317 This should excercise most of the new code.

318 """

319 results = self.task.run(self.inputMeasurements, self.camera, self.inputDims, self.ptc)

320

321 calib = results.outputCalib

322

323 for key, value in self.sequencerMetadata.items():

324 self.assertEqual(calib.metadata[key], value)

325

326 for key in ["INSTRUME", "DETECTOR", "DET_NAME", "DET_SER"]:

327 self.assertEqual(calib.metadata[key], self.ptc.metadata[key])

328

329 # Check that the signals array is sorted

330 for ampName in calib.signals.keys():

331 assert numpy.all(numpy.diff(calib.signals[ampName]) > 0)

332

333 # Check that the result matches expectation.

334 self.assertAlmostEqual(calib.globalCti['C:0,0'], 1.0e-7, 4)

335 self.assertAlmostEqual(calib.driftScale['C:0,0'], 1.8105e-4, 4)

336 self.assertAlmostEqual(calib.decayTime['C:0,0'], 3.08095, 4)

337

338 # Check that all amps are equal.

339 for ampName in calib.globalCti.keys():

340 self.assertEqual(calib.globalCti['C:0,0'], calib.globalCti[ampName])

341 self.assertEqual(calib.driftScale['C:0,0'], calib.driftScale[ampName])

342 self.assertEqual(calib.decayTime['C:0,0'], calib.decayTime[ampName])

343 self.assertEqual(calib.signals[ampName][-2], calib.serialCtiTurnoff[ampName])

344 self.assertEqual(calib.signals[ampName][-1], calib.parallelCtiTurnoff[ampName])

345 self.assertEqual(

346 (calib.signals[ampName][-1] - calib.signals[ampName][-3]) / 2.0,

347 calib.serialCtiTurnoffSamplingErr[ampName],

348 )

349 self.assertEqual(

350 calib.signals[ampName][-1] - calib.signals[ampName][-2],

351 calib.parallelCtiTurnoffSamplingErr[ampName],

352 )

353

354

355class TestMemory(lsst.utils.tests.MemoryTestCase):

356 pass

357

358

359def setup_module(module):

360 lsst.utils.tests.init()

361

362

363if __name__ == "__main__": 363 ↛ 364line 363 didn't jump to line 364 because the condition on line 363 was never true

364 lsst.utils.tests.init()

365 unittest.main()

Coverage for tests / test_deferredCharge.py: 24%

48 statements