Coverage for C: \ Users \ peaco \ OneDrive \ Documents \ GitHub \ mt_metadata \ mt_metadata \ transfer_functions \ tf \ transfer_function.py: 88%
40 statements
« prev ^ index » next coverage.py v7.13.1, created at 2026-01-10 00:11 -0800
1# =====================================================
2# Imports
3# =====================================================
4from typing import Annotated
6import numpy as np
7import pandas as pd
8from pydantic import Field, field_validator
10from mt_metadata.base import MetadataBase
11from mt_metadata.common import (
12 AuthorPerson,
13 DataQuality,
14 GeographicReferenceFrameEnum,
15 SignConventionEnum,
16 Software,
17)
18from mt_metadata.common.mttime import MTime
19from mt_metadata.common.units import get_unit_object
22# =====================================================
25class TransferFunction(MetadataBase):
26 id: Annotated[
27 str,
28 Field(
29 default="",
30 description="transfer function id",
31 alias=None,
32 json_schema_extra={
33 "units": None,
34 "required": True,
35 "examples": ["mt01_256"],
36 },
37 ),
38 ]
40 sign_convention: Annotated[
41 SignConventionEnum,
42 Field(
43 default="+",
44 description="sign of the transfer function estimates",
45 alias=None,
46 json_schema_extra={
47 "units": None,
48 "required": True,
49 "examples": ["+"],
50 },
51 ),
52 ]
54 units: Annotated[
55 str,
56 Field(
57 default="milliVolt per kilometer per nanoTesla",
58 description="units of the impedance tensor estimates",
59 alias=None,
60 json_schema_extra={
61 "units": None,
62 "required": True,
63 "examples": ["milliVolt per kilometer per nanoTesla"],
64 },
65 ),
66 ]
68 runs_processed: Annotated[
69 list[str],
70 Field(
71 default=[],
72 description="list of runs used in the processing",
73 alias=None,
74 json_schema_extra={
75 "units": None,
76 "required": True,
77 "examples": [["MT001a", "MT001c"]],
78 },
79 ),
80 ]
82 remote_references: Annotated[
83 list[str],
84 Field(
85 default_factory=list,
86 description="list of remote references",
87 alias=None,
88 json_schema_extra={
89 "units": None,
90 "required": True,
91 "examples": [["MT002b", "MT002c"]],
92 },
93 ),
94 ]
96 processed_date: Annotated[
97 MTime | str | float | int | np.datetime64 | pd.Timestamp,
98 Field(
99 default_factory=lambda: MTime(time_stamp=None),
100 description="date the data were processed",
101 alias=None,
102 json_schema_extra={
103 "units": None,
104 "required": True,
105 "examples": ["2020-01-01T12:00:00"],
106 },
107 ),
108 ]
110 processing_parameters: Annotated[
111 list[str],
112 Field(
113 default_factory=list,
114 description="list of processing parameters with structure name = value",
115 alias=None,
116 json_schema_extra={
117 "units": None,
118 "required": True,
119 "examples": [["nfft=4096", "n_windows=16"]],
120 },
121 ),
122 ]
124 processed_by: Annotated[
125 AuthorPerson,
126 Field(
127 default_factory=AuthorPerson, # type: ignore
128 description="person who processed the data",
129 alias=None,
130 json_schema_extra={
131 "units": None,
132 "required": True,
133 "examples": ["Person(name='John Doe', email='john.doe@example.com')"],
134 },
135 ),
136 ]
138 processing_type: Annotated[
139 str,
140 Field(
141 default="",
142 description="Type of processing",
143 alias=None,
144 json_schema_extra={
145 "units": None,
146 "required": True,
147 "examples": ["robust remote reference"],
148 },
149 ),
150 ]
152 software: Annotated[
153 Software,
154 Field(
155 default_factory=Software, # type: ignore
156 description="software used to process the data",
157 alias=None,
158 json_schema_extra={
159 "units": None,
160 "required": True,
161 "examples": ["Software(name='Aurora', version='1.0.0')"],
162 },
163 ),
164 ]
166 data_quality: Annotated[
167 DataQuality,
168 Field(
169 default_factory=DataQuality, # type: ignore
170 description="data quality information",
171 alias=None,
172 json_schema_extra={
173 "units": None,
174 "required": True,
175 "examples": ["DataQuality()"],
176 },
177 ),
178 ]
180 coordinate_system: Annotated[
181 GeographicReferenceFrameEnum,
182 Field(
183 default=GeographicReferenceFrameEnum.geographic,
184 description="coordinate system that the transfer function is in. It is strongly recommended that the transfer functions be rotated to align with geographic coordinates with geographic north as 0 and east as 90.",
185 alias=None,
186 json_schema_extra={
187 "units": None,
188 "required": True,
189 "examples": ["geographic"],
190 },
191 ),
192 ]
194 # this will evenutally be config objects for the various processing programs
195 # e.g. aurora, razorback, resistics, etc.
196 # for now it is just a string
197 processing_config: Annotated[
198 str | None,
199 Field(
200 default=None,
201 description="processing configuration",
202 alias=None,
203 json_schema_extra={
204 "units": None,
205 "required": False,
206 "examples": ["aurora.processing"],
207 },
208 ),
209 ]
211 @field_validator("processed_date", mode="before")
212 @classmethod
213 def validate_processed_date(
214 cls, field_value: MTime | float | int | np.datetime64 | pd.Timestamp | str
215 ):
216 if isinstance(field_value, MTime):
217 return field_value
218 return MTime(time_stamp=field_value)
220 @field_validator("units", mode="before")
221 @classmethod
222 def validate_units(cls, value: str) -> str:
223 if value in [None, ""]:
224 return ""
225 try:
226 unit_object = get_unit_object(value)
227 return unit_object.name
228 except ValueError as error:
229 raise KeyError(error)
230 except KeyError as error:
231 raise KeyError(error)