Coverage for python/lsst/analysis/tools/actions/keyedData/summaryStatistics.py: 71%

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1# This file is part of analysis_tools. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

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

21from __future__ import annotations 

22 

23from functools import partial 

24 

25import scipy.stats as sps 

26from lsst.pex.config import Field 

27 

28from ...interfaces import KeyedData 

29from ..scalar import CountAction, MedianAction, SigmaMadAction 

30from .keyedDataActions import KeyedScalars 

31 

32__all__ = ( 

33 "sigmaMad", 

34 "SummaryStatisticAction", 

35) 

36 

37sigmaMad = partial(sps.median_abs_deviation, scale="normal") # type: ignore 

38 

39 

40class SummaryStatisticAction(KeyedScalars): 

41 vectorKey = Field[str](doc="Column key to compute scalars") 

42 

43 def setDefaults(self): 

44 super().setDefaults() 

45 self.scalarActions.median = MedianAction(vectorKey=self.vectorKey) 

46 self.scalarActions.sigmaMad = SigmaMadAction(vectorKey=self.vectorKey) 

47 self.scalarActions.count = CountAction(vectorKey=self.vectorKey) 

48 

49 def __call__(self, data: KeyedData, **kwargs) -> KeyedData: 

50 mask = kwargs.get("mask") 

51 return super().__call__(data, **(kwargs | dict(mask=mask)))