Coverage for C: \ Users \ peaco \ OneDrive \ Documents \ GitHub \ mt_metadata \ mt_metadata \ transfer_functions \ tf \ __init__.py: 100%

1# -*- coding: utf-8 -*- 

2""" 

3================== 

4metadata 

5================== 

6 

7This module deals with metadata as defined by the MT metadata standards. 

8`metadata documentation 

9<https://github.com/kujaku11/MTarchive/blob/tables/docs/mt_metadata_guide.pdf>`_. 

10 

11There are multiple containers for each type of metadata, named appropriately. 

12 

13Each container will be able to read and write: 

14 * dictionary 

15 * json 

16 * xml 

17 * csv? 

18 * pandas.Series 

19 * anything else? 

20 

21Because a lot of the name words in the metadata are split by '.' there are some 

22issues we need to deal with. I wrote in get and set attribute functions 

23to handle these types of names so the user shouldn't have to work about 

24splitting the names themselves. 

25 

26These containers will be the building blocks for the metadata and how they are 

27interchanged between the HDF5 file and the user. A lot of the metadata you 

28can get directly from the raw time series files, but the user will need to 

29input a decent amount on their own. Dictionaries are the most fundamental 

30type we should be dealing with. 

31 

32Each container has an attribute called _attr_dict which dictates if the 

33attribute is included in output objects, the data type, whether it is a 

34required parameter, and the style of output. This should help down the road 

35with validation and keeping the data types consistent. And if things change 

36you should only have to changes these dictionaries. 

37 

38self._attr_dict = {'nameword':{'type': str, 'required': True, 'style': 'name'}} 

39 

40Created on Sun Apr 24 20:50:41 2020 

41 

42:copyright: 

43 Jared Peacock (jpeacock@usgs.gov) 

44 

45:license: 

46 MIT 

47 

48 

49""" 

50# isort:skip_file 

51# package file 

52from .transfer_function import TransferFunction 

53from .station import Station 

54 

55 

56__all__ = [ 

57 "TransferFunction", 

58 "Station", 

59]