Coverage for python/lsst/analysis/tools/actions/plot/calculateRange.py: 62%

16 statements  

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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/>. 

21 

22from __future__ import annotations 

23 

24__all__ = ("MinMax", "Med2Mad") 

25 

26from typing import cast 

27 

28import numpy as np 

29 

30from ...interfaces import Vector, VectorAction 

31from ...statistics import nansigmaMad 

32 

33 

34class MinMax(VectorAction): 

35 """Return the maximum and minimum values of an input vector to use as the 

36 minimum and maximum values of a colorbar range. 

37 

38 Parameters 

39 ---------- 

40 data : `Vector` 

41 A vector containing the data whose minimum and maximum are to be 

42 returned. 

43 

44 Returns 

45 ------- 

46 A two-element vector containing the minimum and maximum values of `data`. 

47 """ 

48 

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

50 return cast(Vector, [np.min(data), np.max(data)]) 

51 

52 

53class Med2Mad(VectorAction): 

54 """Return the median +/- 2*nansigmamad values of an input vector to use 

55 as the minimum and maximum values of a colorbar range. 

56 

57 Parameters 

58 ---------- 

59 data : `Vector` 

60 A vector containing the data whose median +/- 2*nansigmamad are to 

61 be returned. 

62 

63 Returns 

64 ------- 

65 A two-element vector containing the median +/- 2*nansigmamad values of 

66 `data`. 

67 """ 

68 

69 def __call__(self, data: Vector, **kwargs) -> Vector: 

70 med = np.nanmedian(data) 

71 mad = nansigmaMad(data) 

72 cmin = med - 2 * mad 

73 cmax = med + 2 * mad 

74 return cast(Vector, [cmin, cmax])