def test_get_response(self):
response_n1_s1 = Response('RESPN1S1')
response_n1_s2 = Response('RESPN1S2')
response_n2_s1 = Response('RESPN2S1')
channels_n1_s1 = [
Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n1_s1)
]
channels_n1_s2 = [
Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n1_s2)
]
channels_n2_s1 = [
Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n2_s1)
]
stations_1 = [
Station(code='N1S1',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n1_s1),
Station(code='N1S2',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n1_s2),
Station(code='N2S1',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n2_s1)
]
network = Network('N1', stations=stations_1)
response = network.get_response('N1.N1S1..BHZ',
UTCDateTime('2010-01-01T12:00'))
self.assertEqual(response, response_n1_s1)
response = network.get_response('N1.N1S2..BHZ',
UTCDateTime('2010-01-01T12:00'))
self.assertEqual(response, response_n1_s2)
response = network.get_response('N1.N2S1..BHZ',
UTCDateTime('2010-01-01T12:00'))
self.assertEqual(response, response_n2_s1)
def test_get_response(self):
response_n1_s1 = Response('RESPN1S1')
response_n1_s2 = Response('RESPN1S2')
response_n2_s1 = Response('RESPN2S1')
channels_n1_s1 = [Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n1_s1)]
channels_n1_s2 = [Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n1_s2)]
channels_n2_s1 = [Channel(code='BHZ',
location_code='',
latitude=0.0,
longitude=0.0,
elevation=0.0,
depth=0.0,
response=response_n2_s1)]
stations_1 = [Station(code='N1S1',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n1_s1),
Station(code='N1S2',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n1_s2)]
stations_2 = [Station(code='N2S1',
latitude=0.0,
longitude=0.0,
elevation=0.0,
channels=channels_n2_s1)]
networks = [Network('N1', stations=stations_1),
Network('N2', stations=stations_2)]
inv = Inventory(networks=networks, source='TEST')
response = inv.get_response('N1.N1S1..BHZ',
UTCDateTime('2010-01-01T12:00'))
assert response == response_n1_s1
response = inv.get_response('N1.N1S2..BHZ',
UTCDateTime('2010-01-01T12:00'))
assert response == response_n1_s2
response = inv.get_response('N2.N2S1..BHZ',
UTCDateTime('2010-01-01T12:00'))
assert response == response_n2_s1
def geophone_response(resonance_frequency,
gain,
damping=0.707,
output_resistance=np.inf,
cable_length=np.inf,
cable_capacitance=np.inf,
sensitivity=1,
stage_sequence_number=1):
paz = corn_freq_2_paz(resonance_frequency, damp=damping)
l = cable_length
R = output_resistance
C = cable_capacitance
if ((R * l * C) != np.inf) and ((R * l * C) != 0):
pole_cable = -1 / (R * l * C)
paz['poles'].append(pole_cable)
i_s = InstrumentSensitivity(sensitivity,
resonance_frequency,
input_units='M/S',
output_units='M/S',
input_units_description='velocity',
output_units_description='velocity')
pzr = PolesZerosResponseStage(stage_sequence_number, gain,
resonance_frequency, 'M/S', 'M/S',
'LAPLACE (RADIANT/SECOND)',
resonance_frequency, paz['zeros'],
paz['poles'])
return Response(instrument_sensitivity=i_s, response_stages=[pzr])
def _channel_from_stats(stats):
if stats.standard.units in UNITS:
units = UNITS[stats.standard.units]
else:
units = ''
instrument = stats.standard.instrument
serialnum = stats.standard.sensor_serial_number
if len(instrument) or len(serialnum):
equipment = Equipment(type=instrument,
serial_number=serialnum)
else:
equipment = None
depth = 0.0
azimuth = None
c1 = 'horizontal_orientation' in stats.standard
c2 = c1 and not np.isnan(stats.standard.horizontal_orientation)
if c2:
azimuth = stats.standard.horizontal_orientation
else:
azimuth = 0
if not (azimuth >= 0 and azimuth <= 360):
azimuth = 0
response = None
if 'response' in stats:
response = stats['response']
else:
# we may have instrument sensitivity...
frequency = 1 / stats['standard']['instrument_period']
units = stats.standard.units
if not np.isnan(stats['standard']['instrument_sensitivity']):
sens = stats['standard']['instrument_sensitivity']
else:
sens = 1.0
sensitivity = InstrumentSensitivity(sens,
frequency=frequency,
input_units=units,
output_units='COUNTS')
response = Response(instrument_sensitivity=sensitivity)
comments = Comment(stats.standard.comments)
logging.debug('channel: %s' % stats.channel)
channel = Channel(stats.channel,
stats.location,
stats.coordinates['latitude'],
stats.coordinates['longitude'],
stats.coordinates['elevation'],
depth,
azimuth=azimuth,
sample_rate=stats.sampling_rate,
storage_format=stats.standard.source_format,
calibration_units=units,
comments=[comments],
response=response,
sensor=equipment)
return channel
def _channel_from_stats(stats):
if stats.standard.units in UNITS:
units = UNITS[stats.standard.units]
else:
units = ""
instrument = stats.standard.instrument
serialnum = stats.standard.sensor_serial_number
if len(instrument) or len(serialnum):
equipment = Equipment(type=instrument, serial_number=serialnum)
else:
equipment = None
depth = 0.0
azimuth = None
c1 = "horizontal_orientation" in stats.standard
c2 = c1 and not np.isnan(stats.standard.horizontal_orientation)
if c2:
azimuth = stats.standard.horizontal_orientation
else:
azimuth = 0
if not (azimuth >= 0 and azimuth <= 360):
azimuth = 0
response = None
if "response" in stats:
response = stats["response"]
else:
# we may have instrument sensitivity...
frequency = 1 / stats["standard"]["instrument_period"]
units = stats.standard.units
if not np.isnan(stats["standard"]["instrument_sensitivity"]):
sens = stats["standard"]["instrument_sensitivity"]
else:
sens = 1.0
sensitivity = InstrumentSensitivity(sens,
frequency=frequency,
input_units=units,
output_units="COUNTS")
response = Response(instrument_sensitivity=sensitivity)
comments = Comment(stats.standard.comments)
logging.debug(f"channel: {stats.channel}")
channel = Channel(
stats.channel,
stats.location,
stats.coordinates["latitude"],
stats.coordinates["longitude"],
stats.coordinates["elevation"],
depth,
azimuth=azimuth,
sample_rate=stats.sampling_rate,
calibration_units=units,
comments=[comments],
response=response,
sensor=equipment,
)
return channel
def test_ppsd_time_checks(self):
"""
Some tests that make sure checking if a new PSD slice to be addded to
existing PPSD has an invalid overlap or not works as expected.
"""
ppsd = PPSD(Stats(), Response())
one_second = 1000000000
t0 = 946684800000000000 # 2000-01-01T00:00:00
time_diffs = [
0, one_second, one_second * 2, one_second * 3, one_second * 8,
one_second * 9, one_second * 10
]
ppsd._times_processed = [t0 + td for td in time_diffs]
ppsd.ppsd_length = 2
ppsd.overlap = 0.5
# valid time stamps to insert data for (i.e. data that overlaps with
# existing data at most "overlap" times "ppsd_length")
ns_ok = [
t0 - 3 * one_second,
t0 - 1.01 * one_second,
t0 - one_second,
t0 + 4 * one_second,
t0 + 4.01 * one_second,
t0 + 6 * one_second,
t0 + 7 * one_second,
t0 + 6.99 * one_second,
t0 + 11 * one_second,
t0 + 11.01 * one_second,
t0 + 15 * one_second,
]
for ns in ns_ok:
t = UTCDateTime(ns=int(ns))
# getting False means time is not present yet and a PSD slice would
# be added to the PPSD data
self.assertFalse(ppsd._PPSD__check_time_present(t))
# invalid time stamps to insert data for (i.e. data that overlaps with
# existing data more than "overlap" times "ppsd_length")
ns_bad = [
t0 - 0.99 * one_second,
t0 - 0.5 * one_second,
t0,
t0 + 1.1 * one_second,
t0 + 3.99 * one_second,
t0 + 7.01 * one_second,
t0 + 7.5 * one_second,
t0 + 8 * one_second,
t0 + 8.8 * one_second,
t0 + 10 * one_second,
t0 + 10.99 * one_second,
]
for ns in ns_bad:
t = UTCDateTime(ns=int(ns))
# getting False means time is not present yet and a PSD slice would
# be added to the PPSD data
self.assertTrue(ppsd._PPSD__check_time_present(t))
def accelerometer_response(resonance_frequency,
gain,
sensitivity=1,
stage_sequence_number=1,
damping=0.707):
i_s = InstrumentSensitivity(sensitivity,
resonance_frequency,
input_units='M/S/S',
output_units='M/S/S',
input_units_description='acceleration',
output_units_description='acceleration')
paz = corn_freq_2_paz(resonance_frequency, damp=damping)
paz['zeros'] = []
pzr = PolesZerosResponseStage(1, 1, 14, 'M/S/S', 'M/S',
'LAPLACE (RADIANT/SECOND)', 1, [],
paz['poles'])
return Response(instrument_sensitivity=i_s, response_stages=[pzr])
def read_fdsn_station_text_file(path_or_file_object):
"""
Function reading a FDSN station text file to an inventory object.
:param path_or_file_object: File name or file like object.
"""
def _read(obj):
r = unicode_csv_reader(obj, delimiter=native_str("|"))
header = next(r)
header[0] = header[0].lstrip("#")
header = [_i.strip().lower() for _i in header]
# IRIS currently has a wrong header name. Just map it.
header = [
_i.replace("instrument", "sensordescription") for _i in header
]
all_lines = []
for line in r:
# Skip comment lines.
if line[0].startswith("#"):
continue
all_lines.append([_i.strip() for _i in line])
return {"header": tuple(header), "content": all_lines}
# Enable reading from files and buffers opened in binary mode.
if (hasattr(path_or_file_object, "mode") and
"b" in path_or_file_object.mode) or \
isinstance(path_or_file_object, io.BytesIO):
buf = io.StringIO(path_or_file_object.read().decode("utf-8"))
buf.seek(0, 0)
path_or_file_object = buf
if hasattr(path_or_file_object, "read"):
content = _read(path_or_file_object)
else:
with open(path_or_file_object, "rt", newline="",
encoding="utf8") as fh:
content = _read(fh)
# Figure out the type.
if content["header"] == network_components:
level = "network"
filetypes = network_types
elif content["header"] == station_components:
level = "station"
filetypes = station_types
elif content["header"] == channel_components:
level = "channel"
filetypes = channel_types
else:
raise ValueError("Unknown type of header.")
content = content["content"]
converted_content = []
# Convert all types.
for line in content:
converted_content.append(
[v_type(value) for value, v_type in zip(line, filetypes)])
# Now convert to an inventory object.
inv = Inventory(networks=[], source=None)
if level == "network":
for net in converted_content:
network = Network(code=net[0],
description=net[1],
start_date=net[2],
end_date=net[3],
total_number_of_stations=net[4])
inv.networks.append(network)
elif level == "station":
networks = collections.OrderedDict()
for sta in converted_content:
site = Site(name=sta[5])
station = Station(code=sta[1],
latitude=sta[2],
longitude=sta[3],
elevation=sta[4],
site=site,
start_date=sta[6],
end_date=sta[7])
if sta[0] not in networks:
networks[sta[0]] = []
networks[sta[0]].append(station)
for network_code, stations in networks.items():
net = Network(code=network_code, stations=stations)
inv.networks.append(net)
elif level == "channel":
networks = collections.OrderedDict()
stations = collections.OrderedDict()
for channel in converted_content:
net, sta, loc, chan, lat, lng, ele, dep, azi, dip, inst, scale, \
scale_freq, scale_units, s_r, st, et = channel
if net not in networks:
networks[net] = Network(code=net)
if (net, sta) not in stations:
station = Station(code=sta,
latitude=lat,
longitude=lng,
elevation=ele)
networks[net].stations.append(station)
stations[(net, sta)] = station
sensor = Equipment(type=inst)
if scale is not None and scale_freq is not None:
resp = Response(instrument_sensitivity=InstrumentSensitivity(
value=scale,
frequency=scale_freq,
input_units=scale_units,
output_units=None))
else:
resp = None
try:
channel = Channel(code=chan,
location_code=loc,
latitude=lat,
longitude=lng,
elevation=ele,
depth=dep,
azimuth=azi,
dip=dip,
sensor=sensor,
sample_rate=s_r,
start_date=st,
end_date=et,
response=resp)
except Exception as e:
warnings.warn(
"Failed to parse channel %s.%s.%s.%s due to: %s" %
(net, sta, loc, chan, str(e)), UserWarning)
continue
stations[(net, sta)].channels.append(channel)
inv.networks.extend(list(networks.values()))
else:
# Cannot really happen - just a safety measure.
raise NotImplementedError("Unknown level: %s" % str(level))
return inv
def getStation(stationBlock, units, transFuncs):
## Should probably do a check up here to see that the order given in block is consistent ##
for entry in stationBlock:
if entry.name == 'Station Identifier':
# print 'NewStation!',entry.station_call_letters
staDict = {
'code': entry.station_call_letters,
'latitude': entry.latitude,
'longitude': entry.longitude,
'elevation': entry.elevation,
'channels': [],
'site': Site(entry.site_name),
'creation_date':
UTCDateTime(entry.start_effective_date), # Allows for save
'start_date': UTCDateTime(entry.start_effective_date),
'end_date': UTCDateTime(entry.end_effective_date)
}
staNetCode = entry.network_code
# If found a new channel, reset the stages
elif entry.name == 'Channel Identifier':
# print 'NewChannel!',entry.channel_identifier
stages = []
chaDict = {
'code': entry.channel_identifier,
'location_code': entry.location_identifier,
'latitude': entry.latitude,
'longitude': entry.longitude,
'elevation': entry.elevation,
'depth': entry.local_depth,
'sample_rate': entry.sample_rate,
'start_date': UTCDateTime(entry.start_date),
'end_date': UTCDateTime(entry.end_date),
'azimuth': entry.azimuth,
'dip': entry.dip
}
#code, location_code, latitude, longitude, elevation, depth
# If on a new stage, set up the dictionary again
# ...paz stage
elif entry.name == 'Response Poles and Zeros':
# Get units
stageReqs = {}
# print entry.name,entry.stage_sequence_number
# print entry
# quit()
stageReqs['input_units'] = units[entry.stage_signal_input_units]
stageReqs['output_units'] = units[entry.stage_signal_output_units]
# Collect the poles and zeros
lastType = 'paz'
if entry.number_of_complex_zeros == 0:
zeros = np.array([], dtype=float)
else:
zeros = np.array(entry.real_zero, dtype=float) + np.array(
entry.imaginary_zero, dtype=float) * 1j
if entry.number_of_complex_poles == 0:
poles = np.array([], dtype=float)
else:
poles = np.array(entry.real_pole, dtype=float) + np.array(
entry.imaginary_pole, dtype=float) * 1j
# Form the paz response dictionary (also ensure arrays are 1D)
pazDict = {
'pz_transfer_function_type':
transFuncs[entry.transfer_function_types],
'normalization_factor':
entry.A0_normalization_factor,
'normalization_frequency':
entry.normalization_frequency,
'zeros':
setArrDim(zeros),
'poles':
setArrDim(poles)
}
# ...coeff stage
elif entry.name == 'Response Coefficients':
# Get units
stageReqs = {}
# print entry.name,entry.stage_sequence_number
stageReqs['input_units'] = units[entry.signal_input_units]
stageReqs['output_units'] = units[entry.signal_output_units]
# Collect the coefficients
lastType = 'coef'
if entry.number_of_denominators == 0:
denom = np.array([], dtype=float)
denomErr = np.array([], dtype=float)
else:
denom = np.array(entry.denominator_coefficient, dtype=float)
denomErr = np.array(entry.denominator_error, dtype=float)
if entry.number_of_numerators == 0:
numer = np.array([], dtype=float)
numerErr = np.array([], dtype=float)
else:
numer = np.array(entry.numerator_coefficient, dtype=float)
numerErr = np.array(entry.numerator_error, dtype=float)
# Convert these arrays into lists of numbers which have uncertainty (also ensure arrays are 1D)
denomArr = genArrWithUncertainty(setArrDim(denom),
setArrDim(denomErr))
numerArr = genArrWithUncertainty(setArrDim(numer),
setArrDim(numerErr))
# Form the coeefficient response dictionary
coefDict = {
'cf_transfer_function_type': transFuncs[entry.response_type],
'numerator': numerArr,
'denominator': denomArr
}
# Get the decimation sampling info
elif entry.name == 'Decimation':
# print entry.name,entry.stage_sequence_number
stageReqs['decimation_input_sample_rate'] = Frequency(
entry.input_sample_rate)
stageReqs['decimation_factor'] = entry.decimation_factor
stageReqs['decimation_offset'] = entry.decimation_offset
stageReqs['decimation_delay'] = FloatWithUncertaintiesAndUnit(
entry.estimated_delay)
stageReqs['decimation_correction'] = FloatWithUncertaintiesAndUnit(
entry.correction_applied)
# Get the stage sensitivity
elif entry.name == 'Channel Sensitivity Gain':
# print entry.name,entry.stage_sequence_number
if entry.stage_sequence_number != 0:
stageReqs[
'stage_sequence_number'] = entry.stage_sequence_number
stageReqs['stage_gain'] = entry.sensitivity_gain
stageReqs['stage_gain_frequency'] = entry.frequency
# See what type of stage this was
if lastType == 'paz':
pazDict.update(stageReqs)
stages.append(PolesZerosResponseStage(**pazDict))
else:
coefDict.update(stageReqs)
stages.append(CoefficientsTypeResponseStage(**coefDict))
# If on the last stage, send off the collected stage info
else:
if len(stages) > 0:
instrSens = InstrumentSensitivity(entry.sensitivity_gain,
entry.frequency,
stages[0].input_units,
stages[-1].output_units)
# Finalize the channel dictionary, and append this channel to the station dictionary
chaResp = Response(response_stages=stages,
instrument_sensitivity=instrSens)
chaDict['response'] = chaResp
staDict['channels'].append(Channel(**chaDict))
# Return the stations to the list of stations (also track the network code)
return Station(**staDict), staNetCode
def surf_stations_to_inv(excel_file, debug=0):
"""
Take Petrs orientation excel file for the hydrophones/accelerometers
and build an inventory for later use.
:param excel_file: path to Petr's excel file (formatting hard-coded)
:return: obspy.core.Inventory
"""
# Call coordinate converter
converter = SURF_converter()
sta_df = pd.read_excel(excel_file,
skiprows=[0, 1, 2, 3],
header=1,
nrows=90)
# Assemble dictionary of {station: {channel: infoz}}
# Create dict before, then build inventory from channel level upwards
sta_dict = {}
extra_dict = {}
for i, row in sta_df.iterrows():
# Station location
# Convert from SURF coords to lat lon, but keep local for actual use
lon, lat, elev = converter.to_lonlat(
(row['Easting(m)'], row['Northing(m)'], row['Elev(m)']))
# Correct for arbitrary zero 'depth' of 130m
elev -= 130
# Already accounted for in the elevation but will include here as its
# ...a required arg for Channel()
depth = row['Depth (m)']
# Save HMC coords to custom attributes of Station and Channel
extra = AttribDict({
'hmc_east': {
'value': row['Easting(m)'],
'namespace': 'smi:local/hmc'
},
'hmc_north': {
'value': row['Northing(m)'],
'namespace': 'smi:local/hmc'
},
'hmc_elev': {
'value': row['Elev(m)'], # extra will preserve absolute elev
'namespace': 'smi:local/hmc'
}
})
# Sort out azimuth and dip for this channel (if it exists)
if not np.isnan(row['Sx']):
# TODO Something is real effed here. Answers are right though.
dip_rad = np.arcsin(-row['Sz'])
az_rad = np.arcsin(row['Sx'] / np.cos(dip_rad))
dip = np.rad2deg(dip_rad)
az = np.rad2deg(az_rad)
# Force positive
if az < 0:
az += 360.
# Correct
if row['Sx'] < 0 and row['Sy'] < 0:
az -= 270.
az = 270. - az
elif row['Sy'] < 0:
az = 180 - az
if debug > 0:
print(np.array((row['Sx'], row['Sy'], row['Sz'])))
print(az, dip)
if row['Sensor'].endswith(('Z', 'X', 'Y')):
chan = 'XN{}'.format(row['Sensor'][-1])
# Geophones
if row['Sensor'].startswith('G'):
continue
# Accelerometers
else:
no = row['Sensor'].split('_')[1]
sta_name = '{}{}'.format(row['Desc'], no)
if sta_name in ['OB14', 'OT17', 'PDT2', 'PDT5', 'PSB8', 'PST11']:
# These are geode stations only, skip
continue
channel = Channel(code=chan,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
azimuth=az,
dip=dip,
response=Response())
# channel.extra = extra
elif row['Sensor'].startswith('Hydro'):
chan = 'XN1'
sta_name = '{}{}'.format(row['Desc'],
row['Sensor'].split('-')[-1].zfill(2))
channel = Channel(code=chan,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
extra_dict[sta_name] = extra
# channel.extra = extra
if sta_name in sta_dict.keys():
sta_dict[sta_name].append(channel)
else:
sta_dict[sta_name] = [channel]
# Now loop station dict to create inventory
stas = []
for nm, chans in sta_dict.items():
station = Station(code=nm,
latitude=chans[0].latitude,
longitude=chans[0].longitude,
elevation=chans[0].elevation,
channels=chans)
station.extra = extra_dict[nm]
stas.append(station)
# Build inventory
inventory = Inventory(networks=[Network(code='SV', stations=stas)],
source='SURF')
return inventory
def surf_4100_to_inv(location_file, response_inv, plot=False):
"""
Combine the xyz Homestake locations and MMF calibration responses into
an Inventory object for the 4100L
"""
converter = SURF_converter()
sta_df = pd.read_csv(location_file)
inv = Inventory()
serial_map = {'GMF1': '21010', 'GMF2': '21015', 'GMF3': '21027'}
inv.networks = [Network(code='CB')]
for _, row in sta_df.iterrows():
print(row)
sta_code = row['Sensor name']
# Station location
# Convert from SURF coords to lat lon, but keep local for actual use
lon, lat, elev = converter.to_lonlat(
(row['x_ft'] * 0.3048, row['y_ft'] * 0.3048, row['z_ft'] * 0.3048))
print(lon, lat, elev)
# Just leave as zero here and convert HMC feet elevation to m
depth = 0.0
# Save HMC coords to custom attributes of Station and Channel
extra = AttribDict({
'hmc_east': {
'value': row['x_ft'],
'namespace': 'smi:local/hmc'
},
'hmc_north': {
'value': row['y_ft'],
'namespace': 'smi:local/hmc'
},
'hmc_elev': {
'value': row['z_ft'] * 0.3048,
'namespace': 'smi:local/hmc'
}
})
if sta_code.startswith('TS'):
# Hydrophone or CASSM, wet well
if 'SS' in sta_code:
# Cassm (Y for unspecified instrument)
chan_code = 'XY1'
chans = [
Channel(code=chan_code,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
]
else:
# Hydrophone (D), Downhole (H) per SEED manual
chan_code = 'XDH'
chans = [
Channel(code=chan_code,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
]
elif 'S' in sta_code:
# Grouted CASSM
chan_code = 'XY1'
chans = [
Channel(code=chan_code,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
]
else:
# Grouted accelerometer
chans = []
try:
serial = serial_map[sta_code]
except KeyError:
serial = '9999'
for chan_code in ['XNX', 'XNY', 'XNZ']:
# Set samp_rate to 40 kHz so that Nyquist is below max shake f
chan = Channel(code=chan_code,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=0.,
sample_rate=40000.,
sensor=Equipment(
type='IEPE Accelerometer',
description='Piezoelectric accelerometer',
manufacturer='MMF',
model='KS943B.100',
serial_number=serial))
# Apply exact response for the three tested sensors,
# ...otherwise use the average
avg_resp = response_inv.select(
station='AVG', channel=chan_code)[0][0][0].response
chan.response = avg_resp
chans.append(chan)
sta = Station(code=sta_code,
latitude=chans[0].latitude,
longitude=chans[0].longitude,
elevation=chans[0].elevation,
channels=chans)
sta.extra = extra
inv[0].stations.append(sta)
return inv
def fsb_to_inv(path, orientations=False, debug=0):
"""
Take excel file of sensor locations and build an Inventory
:param path: Path to excel spreadsheet
:param orientations: False or dict of orientation info
:param debug:
:return:
"""
inventory = Inventory()
inventory.networks = [Network(code='FS')]
converter = FSB_converter()
sens_dict = read_fsb_asbuilt(path)
# Assemble dictionary of {station: {channel: infoz}}
# Create dict before, then build inventory from channel level upwards
sta_dict = {}
extra_dict = {}
for sta, loc in sens_dict.items():
# Station location
# Convert from SURF coords to lat lon, but keep local for actual use
lon, lat, elev = converter.to_lonlat((loc[0], loc[1], loc[2]))
depth = 0.0 # Until we do any orientations?
# Save HMC coords to custom attributes of Station and Channel
extra = AttribDict({
'ch1903_east': {
'value': loc[0],
'namespace': 'smi:local/hmc'
},
'ch1903_north': {
'value': loc[1],
'namespace': 'smi:local/hmc'
},
'ch1903_elev': {
'value': loc[2], # extra will preserve absolute elev
'namespace': 'smi:local/hmc'
}
})
# Not yet implemented; Pass orientations dict when we do
if orientations:
# TODO Something is real effed here. Answers are right though.
dip_rad = np.arcsin(-orientations[sta]['Sz'])
az_rad = np.arcsin(orientations[sta]['Sx'] / np.cos(dip_rad))
dip = np.rad2deg(dip_rad)
az = np.rad2deg(az_rad)
# Force positive
if az < 0:
az += 360.
# Correct
if orientations[sta]['Sx'] < 0 and orientations[sta]['Sy'] < 0:
az -= 270.
az = 270. - az
elif orientations[sta]['Sy'] < 0:
az = 180 - az
if debug > 0:
print(
np.array((orientations[sta]['Sx'], orientations[sta]['Sy'],
orientations[sta]['Sz'])))
print(az, dip)
try:
if orientations[sta]['Sensor'].endswith(('Z', 'X', 'Y')):
chan = 'XN{}'.format(orientations[sta]['Sensor'][-1])
# Geophones
if orientations[sta]['Sensor'].startswith('G'):
no = orientations[sta]['Sensor'][-3]
# Accelerometers
else:
no = orientations[sta]['Sensor'].split('_')[1]
sta_name = '{}{}'.format(orientations[sta]['Desc'], no)
channel = Channel(code=chan,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
azimuth=az,
dip=dip,
response=Response())
# channel.extra = extra
elif orientations[sta]['Sensor'].startswith('Hydro'):
chan = 'XN1'
sta_name = '{}{}'.format(
orientations[sta]['Desc'],
orientations[sta]['Sensor'].split('-')[-1].zfill(2))
channel = Channel(code=chan,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
except TypeError as e:
sta_name = sta
if sta in fsb_accelerometers:
channels = []
for chan in ['XNZ', 'XNX', 'XNY']:
channels.append(
Channel(code=chan,
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response()))
else:
channel = Channel(code='XN1',
location_code='',
latitude=lat,
longitude=lon,
elevation=elev,
depth=depth,
response=Response())
channels = [channel]
extra_dict[sta_name] = extra
sta_dict[sta_name] = channels
for nm, chans in sta_dict.items():
station = Station(code=nm,
latitude=chans[0].latitude,
longitude=chans[0].longitude,
elevation=chans[0].elevation,
channels=chans)
station.extra = extra_dict[nm]
inventory[0].stations.append(station)
return inventory
def MMF_calibration_to_response(directory, plot=False):
"""
Take directory of MMF calibration spreadsheets and convert to Obspy
inventory object
"""
inv = Inventory(networks=[Network(code='MMF')])
lat = Latitude(0.)
lon = Longitude(0.)
chan_map = {
'Tabellenblatt3': 'X',
'Tabellenblatt4': 'Y',
'Tabellenblatt5': 'Z'
}
calibs = glob('{}/*.xls'.format(directory))
avg_amp = {'XNZ': [], 'XNY': [], 'XNX': []}
avg_phase = {'XNZ': [], 'XNY': [], 'XNX': []}
avg_sensitivity = {'XNZ': [], 'XNY': [], 'XNX': []}
avg_freq = []
for c in calibs:
serial = c.split()[-2]
sta = Station(code=serial[1:],
latitude=lat,
longitude=lon,
elevation=0.)
# Tables slightly shifted for each channel due to comments
dict_xyz = pd.read_excel(c,
sheet_name=['Tabellenblatt3'],
header=14,
usecols=list(np.arange(4, 14)),
nrows=37)
dict_xyz.update(
pd.read_excel(c,
sheet_name=['Tabellenblatt4'],
header=14,
usecols=list(np.arange(5, 15)),
nrows=37))
dict_xyz.update(
pd.read_excel(c,
sheet_name=['Tabellenblatt5'],
header=13,
usecols=list(np.arange(9, 20)),
nrows=37))
# Get array of sensitivities at 80 Hz for X, Y, Z
sens = pd.read_excel(c,
sheet_name=['Tabellenblatt2'],
header=84,
usecols=[27],
nrows=3)['Tabellenblatt2'].values.squeeze()
# mV/m/s**2 to V/m/s**2
sens_dict = {
'Tabellenblatt3': float(sens[0].replace(',', '.')) * 1e-3,
'Tabellenblatt4': float(sens[1].replace(',', '.')) * 1e-3,
'Tabellenblatt5': float(sens[2].replace(',', '.')) * 1e-3
}
# Resp for each channel
for nm, df in dict_xyz.items():
# Dummy channel
chan_code = 'XN{}'.format(chan_map[nm])
# Set samp_rate to 40 kHz so that Nyquist is below max shake freq
chan = Channel(code=chan_code,
location_code='',
latitude=lat,
longitude=lon,
elevation=0.,
depth=0.,
sample_rate=40000.,
sensor=Equipment(
type='IEPE Accelerometer',
description='Piezoelectric accelerometer',
manufacturer='MMF',
model='KS943B.100',
serial_number=serial))
values = df[['[Hz]', '[m/s²]', '[°]']].values
# Add to dict for average channel estimate later
avg_amp[chan_code].append(values[:, 1])
avg_phase[chan_code].append(values[:, 2])
avg_sensitivity[chan_code].append(float(sens_dict[nm]))
avg_freq = values[:, 0]
response_elements = [
ResponseListElement(frequency=values[i][0],
amplitude=values[i][1],
phase=values[i][2])
for i in range(values.shape[0])
]
# Add a value at zero to avoid deconvolution errors
response_elements.insert(
0,
ResponseListElement(frequency=0.,
amplitude=values[0][1],
phase=values[0][2]))
resp_stage = ResponseListResponseStage(
response_list_elements=response_elements,
stage_gain=1,
stage_gain_frequency=80.,
input_units='M/S**2',
output_units='V',
stage_sequence_number=1)
sensitivity = InstrumentSensitivity(value=float(sens_dict[nm]),
frequency=80.,
input_units='M/S**2',
output_units='V',
frequency_range_start=5,
frequency_range_end=15850,
frequency_range_db_variation=3)
response = Response(instrument_sensitivity=sensitivity,
response_stages=[resp_stage])
chan.response = response
sta.channels.append(chan)
# chan.response.plot(min_freq=2.4, sampling_rate=40000.)
inv[0].stations.append(sta)
# Now make an 'average' channel for the other sensors
avg_sta = Station(code='AVG', latitude=lat, longitude=lon, elevation=0.)
for c in ['XNX', 'XNY', 'XNZ']:
chan = Channel(code=c,
location_code='',
latitude=lat,
longitude=lon,
elevation=0.,
depth=0.,
sample_rate=40000.,
sensor=Equipment(
type='IEPE Accelerometer',
description='Piezoelectric accelerometer',
manufacturer='MMF',
model='KS943B.100',
serial_number='9999'))
amp = np.array(avg_amp[c]).mean(axis=0)
pha = np.array(avg_phase[c]).mean(axis=0)
response_elements = [
ResponseListElement(frequency=avg_freq[i],
amplitude=amp[i],
phase=pha[i]) for i in range(avg_freq.size)
]
# Add a value at zero to avoid deconvolution errors
response_elements.insert(
0, ResponseListElement(frequency=0.,
amplitude=amp[0],
phase=pha[0]))
resp_stage = ResponseListResponseStage(
response_list_elements=response_elements,
stage_gain=1,
stage_gain_frequency=80.,
input_units='M/S**2',
output_units='V',
stage_sequence_number=1)
sensitivity = InstrumentSensitivity(value=np.array(
avg_sensitivity[c]).mean(),
frequency=80.,
input_units='M/S**2',
output_units='V',
frequency_range_start=5,
frequency_range_end=15850,
frequency_range_db_variation=3)
response = Response(instrument_sensitivity=sensitivity,
response_stages=[resp_stage])
chan.response = response
avg_sta.channels.append(chan)
inv[0].stations.append(avg_sta)
if plot:
inv.plot_response(min_freq=2.4, plot_degrees=True)
return inv
def test_write_stationtxt(self):
"""
Test writing stationtxt at channel level
"""
# Manually create a test Inventory object.
resp_1 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=0.02,
input_units="M/S",
output_units=None,
value=8.48507E8))
resp_2 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=1.0,
input_units="M/S**2",
output_units=None,
value=53435.4))
resp_3 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=0.03,
input_units="M/S",
output_units=None,
value=6.27252E8))
test_inv = Inventory(
source=None,
networks=[
Network(
code="IU",
start_date=obspy.UTCDateTime("1988-01-01T00:00:00"),
end_date=obspy.UTCDateTime("2500-12-31T23:59:59"),
total_number_of_stations=1,
description="Global Seismograph Network (GSN - IRIS/USGS)",
stations=[
Station(code="ANMO",
latitude=34.9459,
longitude=-106.4572,
elevation=1850.0,
channels=[
Channel(code="BCI",
location_code="",
latitude=34.9459,
longitude=-106.4572,
elevation=1850.0,
depth=100.0,
azimuth=0.0,
dip=0.0,
sample_rate=0.0,
sensor=Equipment(
description=
"Geotech KS-36000-I Borehole "
"Seismometer"),
start_date=obspy.UTCDateTime(
"1989-08-29T00:00:00"),
end_date=obspy.UTCDateTime(
"1995-02-01T00:00:00"),
response=resp_1),
Channel(
code="LNZ",
location_code="20",
latitude=34.9459,
longitude=-106.4572,
elevation=1820.7,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=0.0,
sensor=Equipment(
description="Titan Accelerometer"),
start_date=obspy.UTCDateTime(
"2013-06-20T16:30:00"),
response=resp_2),
]),
]),
Network(
code="6E",
start_date=obspy.UTCDateTime("2013-01-01T00:00:00"),
end_date=obspy.UTCDateTime("2016-12-31T23:59:59"),
total_number_of_stations=1,
description="Wabash Valley Seismic Zone",
stations=[
Station(
code="SH01",
latitude=37.7457,
longitude=-88.1368,
elevation=126.0,
channels=[
Channel(
code="LOG",
location_code="",
latitude=37.7457,
longitude=-88.1368,
elevation=126.0,
depth=0.0,
azimuth=0.0,
dip=0.0,
sample_rate=0.0,
sensor=Equipment(
description="Reftek 130 Datalogger"),
start_date=obspy.UTCDateTime(
"2013-11-23T00:00:00"),
end_date=obspy.UTCDateTime(
"2016-12-31T23:59:59"),
response=resp_3)
]),
])
])
# CHANNEL level test
stio = io.StringIO()
test_inv.write(stio, format="STATIONTXT", level="CHANNEL")
# check contents
content = stio.getvalue()
expected = [
("Network|Station|Location|Channel|Latitude|Longitude|"
"Elevation|Depth|Azimuth|Dip|SensorDescription|Scale|"
"ScaleFreq|ScaleUnits|SampleRate|StartTime|EndTime"),
("IU|ANMO||BCI|34.9459|-106.4572|1850.0|100.0|0.0|"
"0.0|Geotech KS-36000-I Borehole Seismometer|"
"848507000.0|0.02|M/S|0.0|1989-08-29T00:00:00|"
"1995-02-01T00:00:00"),
("IU|ANMO|20|LNZ|34.9459|-106.4572|1820.7|0.0|0.0|"
"-90.0|Titan Accelerometer|53435.4|1.0|M/S**2|0.0|"
"2013-06-20T16:30:00|"),
("6E|SH01||LOG|37.7457|-88.1368|126.0|0.0|0.0|0.0|"
"Reftek 130 Datalogger|627252000.0|0.03|M/S|0.0|"
"2013-11-23T00:00:00|2016-12-31T23:59:59"),
]
num_lines_written = 0
for line in expected:
self.assertIn(line, content)
num_lines_written = num_lines_written + 1
# assert that the number of lines written equals
# the number of lines expected
self.assertEqual(num_lines_written, len(expected))
# STATION level test
stio = io.StringIO()
test_inv.write(stio, format="STATIONTXT", level="STATION")
# check contents
content = stio.getvalue()
expected = [
("Network|Station|Latitude|Longitude|"
"Elevation|SiteName|StartTime|EndTime"),
("IU|ANMO|34.9459|-106.4572|1850.0||"),
("6E|SH01|37.7457|-88.1368|126.0||"),
]
num_lines_written = 0
for line in expected:
self.assertIn(line, content)
num_lines_written = num_lines_written + 1
# assert that the number of lines written equals
# the number of lines expected
self.assertEqual(num_lines_written, len(expected))
# NETWORK level test
stio = io.StringIO()
test_inv.write(stio, format="STATIONTXT", level="NETWORK")
# check contents
content = stio.getvalue()
expected = [
("Network|Description|StartTime|EndTime|TotalStations"),
("IU|Global Seismograph Network (GSN - IRIS/USGS)|"
"1988-01-01T00:00:00|2500-12-31T23:59:59|1"),
("6E|Wabash Valley Seismic Zone|"
"2013-01-01T00:00:00|2016-12-31T23:59:59|1"),
]
num_lines_written = 0
for line in expected:
self.assertIn(line, content)
num_lines_written = num_lines_written + 1
# assert that the number of lines written equals
# the number of lines expected
self.assertEqual(num_lines_written, len(expected))
def test_reading_channel_file(self):
"""
Test reading a file at the channel level.
"""
resp_1 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=0.02,
input_units="M/S",
output_units=None,
value=4.88233E8))
resp_2 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=0.03,
input_units="M/S",
output_units=None,
value=4.98112E8))
resp_3 = Response(
instrument_sensitivity=InstrumentSensitivity(frequency=0.03,
input_units="M/S",
output_units=None,
value=6.27252E8))
# Manually create an expected Inventory object.
expected_inv = Inventory(
source=None,
networks=[
Network(
code="AK",
stations=[
Station(
code="BAGL",
latitude=60.4896,
longitude=-142.0915,
elevation=1470,
channels=[
Channel(
code="LHZ",
location_code="",
latitude=60.4896,
longitude=-142.0915,
elevation=1470,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type="Nanometrics Trillium 240 Sec "
"Response sn 400 and a"),
start_date=obspy.UTCDateTime(
"2013-01-01T00:00:00"),
end_date=obspy.UTCDateTime(
"2599-12-31T23:59:59"),
response=resp_1)
]),
Station(
code="BWN",
latitude=64.1732,
longitude=-149.2991,
elevation=356.0,
channels=[
Channel(
code="LHZ",
location_code="",
latitude=64.1732,
longitude=-149.2991,
elevation=356.0,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type="Nanometrics Trillium 240 Sec "
"Response sn 400 and a"),
start_date=obspy.UTCDateTime(
"2010-07-23T00:00:00"),
end_date=obspy.UTCDateTime(
"2014-05-28T23:59:59"),
response=resp_1),
Channel(
code="LHZ",
location_code="",
latitude=64.1732,
longitude=-149.2991,
elevation=356.0,
depth=1.5,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type="Nanometrics Trillium 120 Sec "
"Response/Quanterra 33"),
start_date=obspy.UTCDateTime(
"2014-08-01T00:00:00"),
end_date=obspy.UTCDateTime(
"2599-12-31T23:59:59"),
response=resp_2)
])
]),
Network(
code="AZ",
stations=[
Station(
code="BZN",
latitude=33.4915,
longitude=-116.667,
elevation=1301.0,
channels=[
Channel(
code="LHZ",
location_code="",
latitude=33.4915,
longitude=-116.667,
elevation=1301.0,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type=
"Streckeisen STS-2 G1/Quanterra 330 "
"Linear Phase Be"),
start_date=obspy.UTCDateTime(
"2010-07-26T17:22:00"),
end_date=obspy.UTCDateTime(
"2013-07-15T21:22:23"),
response=resp_3),
Channel(
code="LHZ",
location_code="",
latitude=33.4915,
longitude=-116.667,
elevation=1301.0,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type=
"Streckeisen STS-2 G1/Quanterra 330 "
"Linear Phase Be"),
start_date=obspy.UTCDateTime(
"2013-07-15T21:22:23"),
end_date=obspy.UTCDateTime(
"2013-10-22T19:30:00"),
response=resp_3),
Channel(
code="LHZ",
location_code="",
latitude=33.4915,
longitude=-116.667,
elevation=1301.0,
depth=0.0,
azimuth=0.0,
dip=-90.0,
sample_rate=1.0,
sensor=Equipment(
type=
"Streckeisen STS-2 G1/Quanterra 330 "
"Linear Phase Be"),
start_date=obspy.UTCDateTime(
"2013-10-22T19:30:00"),
end_date=obspy.UTCDateTime(
"2599-12-31T23:59:59"),
response=resp_3)
])
])
])
# Read from a filename.
filename = os.path.join(self.data_dir, "channel_level_fdsn.txt")
inv = read_fdsn_station_text_file(filename)
inv_obs = obspy.read_inventory(filename)
# Copy creation date as it will be slightly different otherwise.
inv.created = expected_inv.created
inv_obs.created = expected_inv.created
self.assertEqual(inv, expected_inv)
self.assertEqual(inv_obs, expected_inv)
# Read from open file in text mode.
with open(filename, "rt", encoding="utf8") as fh:
inv = read_fdsn_station_text_file(fh)
fh.seek(0, 0)
inv_obs = obspy.read_inventory(fh)
inv.created = expected_inv.created
inv_obs.created = expected_inv.created
self.assertEqual(inv, expected_inv)
self.assertEqual(inv_obs, expected_inv)
# Read from open file in binary mode.
with open(filename, "rb") as fh:
inv = read_fdsn_station_text_file(fh)
fh.seek(0, 0)
inv_obs = obspy.read_inventory(fh)
inv.created = expected_inv.created
inv_obs.created = expected_inv.created
self.assertEqual(inv, expected_inv)
self.assertEqual(inv_obs, expected_inv)
# Read from StringIO.
with open(filename, "rt", encoding="utf8") as fh:
with io.StringIO(fh.read()) as buf:
buf.seek(0, 0)
inv = read_fdsn_station_text_file(buf)
buf.seek(0, 0)
inv_obs = obspy.read_inventory(buf)
inv.created = expected_inv.created
inv_obs.created = expected_inv.created
self.assertEqual(inv, expected_inv)
self.assertEqual(inv_obs, expected_inv)
# Read from BytesIO.
with open(filename, "rb") as fh:
with io.BytesIO(fh.read()) as buf:
buf.seek(0, 0)
inv = read_fdsn_station_text_file(buf)
buf.seek(0, 0)
inv_obs = obspy.read_inventory(buf)
inv.created = expected_inv.created
inv_obs.created = expected_inv.created
self.assertEqual(inv, expected_inv)
self.assertEqual(inv_obs, expected_inv)
