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

27 statements  

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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__ = ['CpVerifyDarkConfig', 'CpVerifyDarkTask'] 

27 

28 

29class CpVerifyDarkConfig(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 self.crImageStatKeywords = {'CR_NOISE': 'STDEV', } # noqa F841 

39 

40 

41class CpVerifyDarkTask(CpVerifyStatsTask): 

42 """Dark verification sub-class, implementing the verify method. 

43 """ 

44 ConfigClass = CpVerifyDarkConfig 

45 _DefaultName = 'cpVerifyDark' 

46 

47 def verify(self, exposure, statisticsDict): 

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

49 

50 Parameters 

51 ---------- 

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

53 The exposure the statistics are from. 

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

55 Dictionary of measured statistics. The inner dictionary 

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

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

58 the mostly likely types). 

59 

60 Returns 

61 ------- 

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

63 A dictionary indexed by the amplifier name, containing 

64 dictionaries of the verification criteria. 

65 success : `bool` 

66 A boolean indicating if all tests have passed. 

67 """ 

68 detector = exposure.getDetector() 

69 ampStats = statisticsDict['AMP'] 

70 verifyStats = {} 

71 success = True 

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

73 verify = {} 

74 

75 # DMTN-101 Test 5.2: Mean is 0.0: 

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

77 

78 # DMTN-101 Test 5.3: Clipped mean matches readNoise 

79 amp = detector[ampName] 

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

81 

82 # DMTN-101 Test 5.4: CR rejection matches clipped mean 

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

84 

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

86 if verify['SUCCESS'] is False: 

87 success = False 

88 

89 verifyStats[ampName] = verify 

90 

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