Coverage for C: \ Users \ peaco \ OneDrive \ Documents \ GitHub \ mth5 \ mth5 \ groups \ filter_groups \ fir_filter_group.py: 93%

1# -*- coding: utf-8 -*- 

2""" 

3Created on Wed Jun 9 08:55:16 2021 

4 

5:copyright: 

6 Jared Peacock (jpeacock@usgs.gov) 

7 

8:license: MIT 

9 

10""" 

11 

12# ============================================================================= 

13# Imports 

14# ============================================================================= 

15 

16 

17from mt_metadata.timeseries.filters import FIRFilter 

18 

19from mth5.groups.base import BaseGroup 

20 

21 

22# ============================================================================= 

23# fir Group 

24# ============================================================================= 

25class FIRGroup(BaseGroup): 

26 """ 

27 Container for fir type filters 

28 

29 """ 

30 

31 def __init__(self, group, **kwargs): 

32 super().__init__(group, **kwargs) 

33 

34 @property 

35 def filter_dict(self): 

36 """ 

37 

38 Dictionary of available fir filters 

39 

40 :return: DESCRIPTION 

41 :rtype: TYPE 

42 """ 

43 f_dict = {} 

44 for key in self.hdf5_group.keys(): 

45 fir_group = self.hdf5_group[key] 

46 f_dict[key] = { 

47 "type": fir_group.attrs["type"], 

48 "hdf5_ref": fir_group.ref, 

49 } 

50 

51 return f_dict 

52 

53 def add_filter(self, name, coefficients, fir_metadata): 

54 """ 

55 create an HDF5 group/dataset from information given. 

56 

57 :param name: Nane of the filter 

58 :type name: string 

59 :param poles: poles of the filter as complex numbers 

60 :type poles: np.ndarray(dtype=complex) 

61 :param zeros: zeros of the filter as complex numbers 

62 :type zeros: np.ndarray(dtype=comples) 

63 :param fir_metadata: metadata dictionary see 

64 :class:`mt_metadata.timeseries.filters.PoleZeroFilter` for details on entries 

65 :type fir_metadata: dictionary 

66 

67 """ 

68 # create a group for the filter by the name 

69 fir_filter_group = self.hdf5_group.create_group(name) 

70 

71 # create datasets for the poles and zeros 

72 fir_ds = fir_filter_group.create_dataset( 

73 "coefficients", 

74 coefficients.shape, 

75 **self.dataset_options, 

76 ) 

77 

78 fir_ds[:] = coefficients 

79 

80 # fill in the metadata 

81 fir_filter_group.attrs.update(fir_metadata) 

82 

83 return fir_filter_group 

84 

85 def remove_filter(self): 

86 pass 

87 

88 def get_filter(self, name): 

89 """ 

90 Get a filter from the name 

91 

92 :param name: name of the filter 

93 :type name: string 

94 

95 :return: HDF5 group of the fir filter 

96 """ 

97 return self.hdf5_group[name] 

98 

99 def from_object(self, fir_object): 

100 """ 

101 make a filter from a :class:`mt_metadata.timeseries.filters.PoleZeroFilter` 

102 

103 :param fir_object: MT metadata PoleZeroFilter 

104 :type fir_object: :class:`mt_metadata.timeseries.filters.PoleZeroFilter` 

105 

106 """ 

107 

108 if not isinstance(fir_object, FIRFilter): 

109 msg = "Filter must be a FrequencyResponseTableFilter not %s" 

110 self.logger.error(msg, type(fir_object)) 

111 raise TypeError(msg) 

112 

113 input_dict = fir_object.to_dict(single=True, required=False) 

114 input_dict.pop("coefficients") 

115 for k, v in input_dict.items(): 

116 if v is None: 

117 input_dict[k] = str(v) 

118 

119 fir_group = self.add_filter( 

120 fir_object.name, 

121 fir_object.coefficients, 

122 input_dict, 

123 ) 

124 return fir_group 

125 

126 def to_object(self, name): 

127 """ 

128 make a :class:`mt_metadata.timeseries.filters.pole_zeros_filter` object 

129 

130 :return: DESCRIPTION 

131 :rtype: TYPE 

132 

133 """ 

134 

135 fir_group = self.get_filter(name) 

136 

137 fir_obj = FIRFilter(**fir_group.attrs) 

138 

139 try: 

140 fir_obj.coefficients = fir_group["coefficients"][:] 

141 except TypeError: 

142 self.logger.debug("fir filter %s has no coefficients", name) 

143 fir_obj.coefficients = [] 

144 

145 return fir_obj