Coverage for python/lsst/daf/butler/instrument.py: 90%

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1# This file is part of daf_butler. 

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/>. 

21 

22__all__ = ["ObservationDimensionPacker"] 

23 

24from lsst.daf.butler import DataCoordinate, DimensionGraph, DimensionPacker 

25 

26 

27class ObservationDimensionPacker(DimensionPacker): 

28 """A `DimensionPacker` for visit+detector or exposure+detector, given an 

29 instrument. 

30 """ 

31 

32 def __init__(self, fixed: DataCoordinate, dimensions: DimensionGraph): 

33 super().__init__(fixed, dimensions) 

34 self._instrumentName = fixed["instrument"] 

35 record = fixed.records["instrument"] 

36 assert record is not None 

37 if self.dimensions.required.names == set(["instrument", "visit", "detector"]): 

38 self._observationName = "visit" 

39 obsMax = record.visit_max 

40 elif dimensions.required.names == set(["instrument", "exposure", "detector"]): 40 ↛ 44line 40 didn't jump to line 44, because the condition on line 40 was never false

41 self._observationName = "exposure" 

42 obsMax = record.exposure_max 

43 else: 

44 raise ValueError(f"Invalid dimensions for ObservationDimensionPacker: {dimensions.required}") 

45 self._detectorMax = record.detector_max 

46 self._maxBits = (obsMax * self._detectorMax).bit_length() 

47 

48 @property 

49 def maxBits(self) -> int: 

50 # Docstring inherited from DimensionPacker.maxBits 

51 return self._maxBits 

52 

53 def _pack(self, dataId: DataCoordinate) -> int: 

54 # Docstring inherited from DimensionPacker._pack 

55 return dataId["detector"] + self._detectorMax * dataId[self._observationName] 

56 

57 def unpack(self, packedId: int) -> DataCoordinate: 

58 # Docstring inherited from DimensionPacker.unpack 

59 observation, detector = divmod(packedId, self._detectorMax) 

60 return DataCoordinate.standardize( 

61 { 

62 "instrument": self._instrumentName, 

63 "detector": detector, 

64 self._observationName: observation, 

65 }, 

66 graph=self.dimensions, 

67 )