diff --git a/geomagio/Controller.py b/geomagio/Controller.py
index 6b95ff5e50983947deafe945e6b7dccb1ca17159..d2d5601cd5aa8fc34e769e78b9ab7260244b5d74 100644
--- a/geomagio/Controller.py
+++ b/geomagio/Controller.py
@@ -334,8 +334,6 @@ def get_input_factory(args):
port=args.input_port,
locationCode=args.locationcode,
convert_channels=args.convert_voltbin,
- volt_conv=args.volt_conversion,
- bin_conv=args.bin_conversion,
**input_factory_args)
elif input_type == 'goes':
# TODO: deal with other goes arguments
@@ -690,14 +688,6 @@ def parse_args(args):
--outchannels U
"
""")
- input_group.add_argument('--volt-conversion',
- default=100.0,
- metavar='NT',
- help='Conversion factor (nT/V) for volts')
- input_group.add_argument('--bin-conversion',
- default=500.0,
- metavar='NT',
- help='Conversion factor (nT/bin) for bins')
# Output group
output_group = parser.add_argument_group('Output', 'How data is written.')
@@ -849,6 +839,15 @@ def parse_args(args):
if '--enable-deprecated-arguments' in args:
add_deprecated_args(deprecated, input_type_group, output_type_group)
+ deprecated.add_argument('--volt-conversion',
+ default=100.0,
+ metavar='NT',
+ help='(Deprecated, Unused) Conversion factor (nT/V) for volts')
+ deprecated.add_argument('--bin-conversion',
+ default=500.0,
+ metavar='NT',
+ help='(Deprecated, Unused) Conversion factor (nT/bin) for bins')
+
return parser.parse_args(args)
diff --git a/geomagio/Metadata.py b/geomagio/Metadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..a6aa0269c1d02e07cbd14510cf759d8ac32c1312
--- /dev/null
+++ b/geomagio/Metadata.py
@@ -0,0 +1,90 @@
+"""Simulate metadata service until it is implemented.
+"""
+
+
+def get_instrument(observatory, start_time=None, end_time=None, metadata=None):
+ """Get instrument metadata
+
+ Args:
+ observatory: observatory code
+ start_time: start time to match, or None to match any.
+ end_time: end time to match, or None to match any.
+ metadata: use custom list, defaults to _INSTRUMENT_METADATA
+ Returns:
+ list of matching metadata
+ """
+ metadata = metadata or _INSTRUMENT_METADATA
+ return [
+ m
+ for m in metadata
+ if m["station"] == observatory and
+ (end_time is None or
+ m["start_time"] is None or
+ m["start_time"] < end_time) and
+ (start_time is None or
+ m["end_time"] is None or
+ m["end_time"] > start_time)
+ ]
+
+
+"""
+To make this list easier to maintain:
+ - List NT network stations first, then other networks in alphabetical order
+ - Within networks, alphabetize by station, then start_time.
+"""
+_INSTRUMENT_METADATA = [
+ {
+ "network": "NT",
+ "station": "BDT",
+ "start_time": None,
+ "end_time": None,
+ "instrument": {
+ "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
+ },
+ },
+ },
+ {
+ "network": "NT",
+ "station": "LLO",
+ "start_time": None,
+ "end_time": None,
+ "instrument": {
+ "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},
+ ],
+ },
+ },
+ },
+]
diff --git a/geomagio/ObservatoryMetadata.py b/geomagio/ObservatoryMetadata.py
index 142170fabd02ea50849e649f2b9ec69795bee899..a35776b8e1c037c6f7c943322671ebb083371e0a 100644
--- a/geomagio/ObservatoryMetadata.py
+++ b/geomagio/ObservatoryMetadata.py
@@ -13,10 +13,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 5527,
- 'fge': True,
- 'U_scale': 313.2,
- 'V_scale': 312.3,
- 'W_scale': 312.0,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -47,10 +43,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 5527,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -81,10 +73,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 10000.0,
'declination_base': 5527,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -115,10 +103,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 10589,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -149,10 +133,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 10000.0,
'declination_base': 10589,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -183,10 +163,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 215772,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -217,10 +193,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 12151,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -238,10 +210,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 10000.0,
'declination_base': 12151,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -259,10 +227,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 10755,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -293,10 +257,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 10000.0,
'declination_base': 10755,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -327,10 +287,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 209690,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -361,10 +317,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 209690,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -395,10 +347,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 8097,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -429,10 +377,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 764,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -463,10 +407,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 5982,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -497,10 +437,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'reported': 'HDZF',
'sensor_sampling_rate': 0.01,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -526,10 +462,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 9547,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -560,10 +492,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 7386,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -594,10 +522,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 12349,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -628,10 +552,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 208439,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -662,10 +582,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 5863,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -696,10 +612,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'sensor_sampling_rate': 100.0,
'declination_base': 0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -726,10 +638,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -755,10 +663,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -784,10 +688,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -813,10 +713,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -842,10 +738,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -871,10 +763,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'reported': 'HDZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -900,10 +788,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'HDZF',
'reported': 'HDZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -929,10 +813,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -958,10 +838,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -987,10 +863,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -1016,10 +888,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -1045,10 +913,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -1074,10 +938,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -1103,10 +963,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
@@ -1132,10 +988,6 @@ DEFAULT_METADATA = {
'sensor_orientation': 'XYZF',
'reported': 'XYZF',
'sensor_sampling_rate': 100.0,
- 'fge': False,
- 'U_scale': 0.,
- 'V_scale': 0.,
- 'W_scale': 0.,
'is_gin': False,
'is_intermagnet': False,
'conditions_of_use': 'The Conditions of Use for data provided' +
diff --git a/geomagio/edge/MiniSeedFactory.py b/geomagio/edge/MiniSeedFactory.py
index 2f9ad74c01fcfbc6d8ea8c8c21cee75b5fb1268c..d95ad4d97c0f47bd486c0760d3194c02af7c9ca8 100644
--- a/geomagio/edge/MiniSeedFactory.py
+++ b/geomagio/edge/MiniSeedFactory.py
@@ -18,6 +18,7 @@ import obspy.core
from obspy.clients.neic import client as miniseed
from .. import ChannelConverter, TimeseriesUtility
+from ..Metadata import get_instrument
from ..TimeseriesFactory import TimeseriesFactory
from ..TimeseriesFactoryException import TimeseriesFactoryException
from ..ObservatoryMetadata import ObservatoryMetadata
@@ -65,7 +66,7 @@ class MiniSeedFactory(TimeseriesFactory):
def __init__(self, host='cwbpub.cr.usgs.gov', port=2061, write_port=7981,
observatory=None, channels=None, type=None, interval=None,
observatoryMetadata=None, locationCode=None,
- convert_channels=None, volt_conv=100, bin_conv=500):
+ convert_channels=None):
TimeseriesFactory.__init__(self, observatory, channels, type, interval)
self.client = miniseed.Client(host, port)
@@ -76,11 +77,7 @@ class MiniSeedFactory(TimeseriesFactory):
self.port = port
self.write_port = write_port
self.convert_channels = convert_channels
- self.volt_conv = volt_conv
- self.bin_conv = bin_conv
self.write_client = MiniSeedInputClient(self.host, self.write_port)
- if isinstance(self.observatory, list) is True:
- self.observatory = self.observatory[0]
def get_timeseries(self, starttime, endtime, observatory=None,
channels=None, type=None, interval=None):
@@ -129,30 +126,17 @@ class MiniSeedFactory(TimeseriesFactory):
# get the timeseries
timeseries = obspy.core.Stream()
for channel in channels:
- data = self._get_timeseries(starttime, endtime, observatory,
- channel, type, interval)
+ if channel in self.convert_channels:
+ data = self._convert_timeseries(starttime, endtime,
+ observatory, channel, type, interval)
+ else:
+ data = self._get_timeseries(starttime, endtime,
+ observatory, channel, type, interval)
timeseries += data
finally:
# restore stdout
sys.stdout = original_stdout
- mdata = self.observatoryMetadata.metadata
- # check for presence of observatory in metadata
- if self.observatory not in mdata.keys():
- fge = False
-
- else:
- fge = mdata[self.observatory]['metadata']['fge']
-
- if self.convert_channels is not None:
- out = obspy.core.Stream()
- for channel in self.convert_channels:
- _in_ = timeseries.select(channel=channel + "_Volt")
- if fge is not True:
- _in_ += timeseries.select(channel=channel + '_Bin')
- out += self.convert_voltbin(channel, _in_)
- timeseries = out
-
self._post_process(timeseries, starttime, endtime, channels)
return timeseries
@@ -199,6 +183,60 @@ class MiniSeedFactory(TimeseriesFactory):
# close socket
self.write_client.close()
+ def get_calculated_timeseries(self, starttime, endtime, observatory,
+ channel, type, interval, components):
+ """Calculate a single channel using multiple component channels.
+
+ Parameters
+ ----------
+ starttime: obspy.core.UTCDateTime
+ the starttime of the requested data
+ endtime: obspy.core.UTCDateTime
+ the endtime of the requested data
+ observatory : str
+ observatory code
+ channel : str
+ single character channel {H, E, D, Z, F}
+ type : str
+ data type {definitive, quasi-definitive, variation}
+ interval : str
+ interval length {'day', 'hour', 'minute', 'second', 'tenhertz'}
+ components: list
+ each component is a dictionary with the following keys:
+ channel: str
+ offset: float
+ scale: float
+
+ Returns
+ -------
+ obspy.core.trace
+ timeseries trace of the converted channel data
+ """
+ # sum channels
+ stats = None
+ converted = None
+ for component in components:
+ # load component
+ data = self._get_timeseries(starttime, endtime, observatory,
+ component["channel"], type, interval)[0]
+ # convert to nT
+ nt = data.data * component["scale"] + component["offset"]
+ # add to converted
+ if converted is None:
+ converted = nt
+ stats = obspy.core.Stats(data.stats)
+ else:
+ converted += nt
+ # set channel parameter to U, V, or W
+ stats.channel = channel
+ # create empty trace with adapted stats
+ out = TimeseriesUtility.create_empty_trace(stats.starttime,
+ stats.endtime, stats.station, stats.channel,
+ stats.data_type, stats.data_interval,
+ stats.network, stats.station, stats.location)
+ out.data = converted
+ return out
+
def _convert_stream_to_masked(self, timeseries, channel):
"""convert geomag edge traces in a timeseries stream to a MaskedArray
This allows for gaps and splitting.
@@ -466,51 +504,57 @@ class MiniSeedFactory(TimeseriesFactory):
observatory, channel, type, interval)
return data
- def convert_voltbin(self, channel, stream):
- """Convert miniseed data from bins and volts to nT.
- Converts all traces in stream.
+ def _convert_timeseries(self, starttime, endtime, observatory,
+ channel, type, interval):
+ """Generate a single channel using multiple components.
+
+ Finds metadata, then calls _get_converted_timeseries for actual
+ conversion.
+
Parameters
----------
- stream: obspy.core.Stream
- stream of data to convert
- channel: string
- channel string(U ,V ,W)
+ starttime: obspy.core.UTCDateTime
+ the starttime of the requested data
+ endtime: obspy.core.UTCDateTime
+ the endtime of the requested data
+ observatory : str
+ observatory code
+ channel : str
+ single character channel {H, E, D, Z, F}
+ type : str
+ data type {definitive, quasi-definitive, variation}
+ interval : str
+ interval length {'day', 'hour', 'minute', 'second', 'tenhertz'}
+
Returns
-------
- out : obspy.core.Trace
- Trace containing 1 trace per 2 original traces.
+ obspy.core.trace
+ timeseries trace of the requested channel data
"""
- out = obspy.core.Trace()
- mdata = self.observatoryMetadata.metadata
- # Checks for presence of observatory in metadata
- if self.observatory not in mdata.keys():
- # selects volts from input Trace
- volts = stream.select(channel=channel + "_Volt")[0]
- # selects bins from input Trace
- bins = stream.select(channel=channel + "_Bin")[0]
- # conversion from bins/volts to nT
- data = self.volt_conv * volts.data \
- + self.bin_conv * bins.data
- else:
- mdata = mdata[self.observatory]['metadata']
- # get scaling factor from observatory metadata
- scale = mdata[channel + '_scale']
- # selects volts from input Trace
- volts = stream.select(channel=channel + "_Volt")[0]
- # conversion from bins/volts to nT
- data = 150 * (volts.data + scale)
-
- # copy stats from original Trace
- stats = obspy.core.Stats(volts.stats)
- # set channel parameter to U, V, or W
- stats.channel = channel
- # create empty trace with adapted stats
- out = TimeseriesUtility.create_empty_trace(stats.starttime,
- stats.endtime, stats.station, stats.channel,
- stats.data_type, stats.data_interval,
- stats.network, stats.station, stats.location)
- # set data for empty trace as nT converted data
- out.data = data
+ out = obspy.core.Stream()
+ metadata = get_instrument(observatory, starttime, endtime)
+ # loop in case request spans different configurations
+ for entry in metadata:
+ entry_endtime = entry["end_time"]
+ entry_starttime = entry["start_time"]
+ instrument = entry["instrument"]
+ instrument_channels = instrument["channels"]
+ if channel not in instrument_channels:
+ # no idea how to convert
+ continue
+ # determine metadata overlap with request
+ start = (starttime
+ if entry_starttime is None or
+ entry_starttime < starttime
+ else entry_starttime)
+ end = (endtime
+ if entry_endtime is None or
+ entry_endtime > endtime
+ else entry_endtime)
+ # now convert
+ out += self.get_calculated_timeseries(start, end,
+ observatory, channel, type, interval,
+ instrument_channels[channel])
return out
def _post_process(self, timeseries, starttime, endtime, channels):
diff --git a/test/Metadata_test.py b/test/Metadata_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..01e5e417144c6b3ac4c1a9557dcea7b07934a8ae
--- /dev/null
+++ b/test/Metadata_test.py
@@ -0,0 +1,79 @@
+from obspy import UTCDateTime
+from geomagio.Metadata import get_instrument
+from numpy.testing import assert_equal
+
+
+METADATA1 = {
+ "station": "TST",
+ "start_time": None,
+ "end_time": UTCDateTime("2020-02-02T00:00:00Z"),
+}
+
+METADATA2 = {
+ "station": "TST",
+ "start_time": UTCDateTime("2020-02-02T00:00:00Z"),
+ "end_time": UTCDateTime("2020-02-03T00:00:00Z"),
+}
+
+METADATA3 = {
+ "station": "TST",
+ "start_time": UTCDateTime("2020-02-03T00:00:00Z"),
+ "end_time": None,
+}
+
+TEST_METADATA = [METADATA1, METADATA2, METADATA3]
+
+
+def test_get_instrument_after():
+ """Request an interval after the last entry, that has start_time None"""
+ matches = get_instrument(
+ "TST",
+ UTCDateTime("2021-02-02T00:00:00Z"),
+ UTCDateTime("2022-01-02T00:00:00Z"),
+ TEST_METADATA,
+ )
+ assert_equal(matches, [METADATA3])
+
+
+def test_get_instrument_before():
+ """Request an interval before the first entry, that has start_time None"""
+ matches = get_instrument(
+ "TST",
+ UTCDateTime("2019-02-02T00:00:00Z"),
+ UTCDateTime("2020-01-02T00:00:00Z"),
+ TEST_METADATA,
+ )
+ assert_equal(matches, [METADATA1])
+
+
+def test_get_instrument_inside():
+ """Request an interval that is wholly contained by one entry"""
+ matches = get_instrument(
+ "TST",
+ UTCDateTime("2020-02-02T01:00:00Z"),
+ UTCDateTime("2020-02-02T02:00:00Z"),
+ TEST_METADATA,
+ )
+ assert_equal(matches, [METADATA2])
+
+
+def test_get_instrument_span():
+ """Request a time interval that spans multiple entries"""
+ matches = get_instrument(
+ "TST",
+ UTCDateTime("2020-01-02T00:00:00Z"),
+ UTCDateTime("2020-02-02T01:00:00Z"),
+ TEST_METADATA,
+ )
+ assert_equal(matches, [METADATA1, METADATA2])
+
+
+def test_get_instrument_unknown():
+ """Request an unknown observatory"""
+ matches = get_instrument(
+ "OTHER",
+ UTCDateTime("2020-01-02T00:00:00Z"),
+ UTCDateTime("2020-02-02T01:00:00Z"),
+ TEST_METADATA,
+ )
+ assert_equal(matches, [])