Coverage for python/lsst/cp/verify/verifyBias.py: 29%

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1# This file is part of cp_verify. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (http://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 <http://www.gnu.org/licenses/>. 

21import numpy as np 

22 

23from .verifyStats import CpVerifyStatsConfig, CpVerifyStatsTask, CpVerifyStatsConnections 

24 

25 

26__all__ = ['CpVerifyBiasConfig', 'CpVerifyBiasTask'] 

27 

28 

29class CpVerifyBiasConfig(CpVerifyStatsConfig, 

30 pipelineConnections=CpVerifyStatsConnections): 

31 """Inherits from base CpVerifyStatsConfig. 

32 """ 

33 

34 def setDefaults(self): 

35 super().setDefaults() 

36 self.imageStatKeywords = {'MEAN': 'MEAN', # noqa F841 

37 'NOISE': 'STDEVCLIP', } 

38 

39 self.crImageStatKeywords = {'CR_NOISE': 'STDEV', } # noqa F841 

40 

41 

42class CpVerifyBiasTask(CpVerifyStatsTask): 

43 """Bias verification sub-class, implementing the verify method. 

44 """ 

45 ConfigClass = CpVerifyBiasConfig 

46 _DefaultName = 'cpVerifyBias' 

47 

48 def verify(self, exposure, statisticsDict): 

49 """Verify that the measured statistics meet the verification criteria. 

50 

51 Parameters 

52 ---------- 

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

54 The exposure the statistics are from. 

55 statisticsDictionary : `dict` [`str`, `dict` [`str`, scalar]], 

56 Dictionary of measured statistics. The inner dictionary 

57 should have keys that are statistic names (`str`) with 

58 values that are some sort of scalar (`int` or `float` are 

59 the mostly likely types). 

60 

61 Returns 

62 ------- 

63 outputStatistics : `dict` [`str`, `dict` [`str`, `bool`]] 

64 A dictionary indexed by the amplifier name, containing 

65 dictionaries of the verification criteria. 

66 success : `bool` 

67 A boolean indicating if all tests have passed. 

68 """ 

69 detector = exposure.getDetector() 

70 ampStats = statisticsDict['AMP'] 

71 

72 verifyStats = {} 

73 success = True 

74 for ampName, stats in ampStats.items(): 

75 verify = {} 

76 

77 # DMTN-101 Test 4.2: Mean is 0.0 within noise. 

78 verify['MEAN'] = bool(np.abs(stats['MEAN']) < stats['NOISE']) 

79 

80 # DMTN-101 Test 4.3: Clipped mean matches readNoise. 

81 amp = detector[ampName] 

82 verify['NOISE'] = bool(np.abs(stats['NOISE'] - amp.getReadNoise())/amp.getReadNoise() <= 0.05) 

83 

84 # DMTN-101 Test 4.4: CR rejection matches clipped mean. 

85 verify['CR_NOISE'] = bool(np.abs(stats['NOISE'] - stats['CR_NOISE'])/stats['CR_NOISE'] <= 0.05) 

86 

87 verify['SUCCESS'] = bool(np.all(list(verify.values()))) 

88 if verify['SUCCESS'] is False: 

89 success = False 

90 

91 verifyStats[ampName] = verify 

92 

93 return {'AMP': verifyStats}, bool(success)