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from geomagio.adjusted import AdjustedMatrix, Metric
from geomagio.api.db import database, MetadataDatabaseFactory
from geomagio.api.ws.Observatory import OBSERVATORIES
from geomagio.metadata import Metadata, MetadataCategory
from geomagio.residual import SpreadsheetAbsolutesFactory, WebAbsolutesFactory
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test_metadata = [
Metadata(
category=MetadataCategory.INSTRUMENT,
created_by="test_metadata.py",
network="NT",
station="BDT",
metadata={
"type": "FGE",
"channels": {
# each channel maps to a list of components to calculate nT
# TODO: calculate these lists based on "FGE" type
"U": [{"channel": "U_Volt", "offset": 0, "scale": 313.2}],
"V": [{"channel": "V_Volt", "offset": 0, "scale": 312.3}],
"W": [{"channel": "W_Volt", "offset": 0, "scale": 312.0}],
},
"electronics": {
"serial": "E0542",
# these scale values are used to convert voltage
"x-scale": 313.2, # V/nT
"y-scale": 312.3, # V/nT
"z-scale": 312.0, # V/nT
"temperature-scale": 0.01, # V/K
},
"sensor": {
"serial": "S0419",
# these constants combine with instrument setting for offset
"x-constant": 36958, # nT/mA
"y-constant": 36849, # nT/mA
"z-constant": 36811, # nT/mA
},
},
),
Metadata(
category=MetadataCategory.INSTRUMENT,
created_by="test_metadata.py",
network="NT",
station="NEW",
metadata={
"type": "Narod",
"channels": {
"U": [
{"channel": "U_Volt", "offset": 0, "scale": 100},
{"channel": "U_Bin", "offset": 0, "scale": 500},
],
"V": [
{"channel": "V_Volt", "offset": 0, "scale": 100},
{"channel": "V_Bin", "offset": 0, "scale": 500},
],
"W": [
{"channel": "W_Volt", "offset": 0, "scale": 100},
{"channel": "W_Bin", "offset": 0, "scale": 500},
],
},
},
),
Metadata(
category=MetadataCategory.INSTRUMENT,
created_by="test_metadata.py",
network="NT",
station="LLO",
metadata={
"type": "Narod",
"channels": {
"U": [
{"channel": "U_Volt", "offset": 0, "scale": 100},
{"channel": "U_Bin", "offset": 0, "scale": 500},
],
"V": [
{"channel": "V_Volt", "offset": 0, "scale": 100},
{"channel": "V_Bin", "offset": 0, "scale": 500},
],
"W": [
{"channel": "W_Volt", "offset": 0, "scale": 100},
{"channel": "W_Bin", "offset": 0, "scale": 500},
],
},
},
),
]
# add observatories
for observatory in OBSERVATORIES:
network = "NT"
if observatory.agency == "USGS":
network = "NT"
# rest alphabetical by agency
elif observatory.agency == "BGS":
network = "GB"
elif observatory.agency == "GSC":
network = "C2"
elif observatory.agency == "JMA":
network = "JP"
elif observatory.agency == "SANSA":
network = "AF"
test_metadata.append(
Metadata(
category=MetadataCategory.OBSERVATORY,
created_by="test_metadata.py",
network=network,
station=observatory.id,
metadata=observatory.dict(),
)
)
readings = WebAbsolutesFactory().get_readings(
observatory="BOU",
starttime=UTCDateTime("2020-01-01"),
endtime=UTCDateTime("2020-01-07"),
)
# get residual reading
reading = SpreadsheetAbsolutesFactory().parse_spreadsheet(
"etc/residual/DED-20140952332.xlsm"
)
readings.append(reading)
for reading in readings:
json_string = reading.json()
reading_dict = json.loads(json_string)
try:
reviewer = reading.metadata["reviewer"]
except KeyError:
reviewer = None
test_metadata.append(
Metadata(
category=MetadataCategory.READING,
created_by="test_metadata.py",
updated_by=reviewer,
endtime=reading.time,
station=reading.metadata["station"],
metadata=reading_dict,
)
)
adjusted_matrix = AdjustedMatrix(
matrix=[
[0.9796103131299191, 0.20090702926851434, 0.0, -18.30071487449033],
[-0.20090702926851361, 0.9796103131299198, 0.0, 406.9685381264491],
[0.0, 0.0, 1.0, 708.4810320770974],
[0.0, 0.0, 0.0, 1.0],
],
pier_correction=-4.0,
metrics=[
Metric(element="X", absmean=0.5365143131738377, stddev=0.7246802312326883),
Metric(element="Y", absmean=1.3338248076759354, stddev=2.1390294659087816),
Metric(element="Z", absmean=0.7020521498941688, stddev=0.8991572596148847),
Metric(element="dF", absmean=0.47978562187806045, stddev=0.5128104930705225),
],
)
test_metadata.append(
Metadata(
category="adjusted-matrix",
station="FRD",
network="NT",
metadata=adjusted_matrix.dict(),
)
async def load_test_metadata():
await database.connect()
for meta in test_metadata:
await MetadataDatabaseFactory(database=database).create_metadata(meta)
await database.disconnect()
if __name__ == "__main__":
import asyncio
asyncio.run(load_test_metadata())