def test_creating_minimal_quakeml_with_mt(self):
"""
Tests the creation of a minimal QuakeML containing origin, magnitude
and moment tensor.
"""
# Rotate into physical domain
lat, lon, depth, org_time = 10.0, -20.0, 12000, UTCDateTime(2012, 1, 1)
mrr, mtt, mpp, mtr, mpr, mtp = 1E18, 2E18, 3E18, 3E18, 2E18, 1E18
scalar_moment = math.sqrt(
mrr ** 2 + mtt ** 2 + mpp ** 2 + mtr ** 2 + mpr ** 2 + mtp ** 2)
moment_magnitude = 0.667 * (math.log10(scalar_moment) - 9.1)
# Initialise event
ev = Event(event_type="earthquake")
ev_origin = Origin(time=org_time, latitude=lat, longitude=lon,
depth=depth, resource_id=ResourceIdentifier())
ev.origins.append(ev_origin)
# populate event moment tensor
ev_tensor = Tensor(m_rr=mrr, m_tt=mtt, m_pp=mpp, m_rt=mtr, m_rp=mpr,
m_tp=mtp)
ev_momenttensor = MomentTensor(tensor=ev_tensor)
ev_momenttensor.scalar_moment = scalar_moment
ev_momenttensor.derived_origin_id = ev_origin.resource_id
ev_focalmechanism = FocalMechanism(moment_tensor=ev_momenttensor)
ev.focal_mechanisms.append(ev_focalmechanism)
# populate event magnitude
ev_magnitude = Magnitude()
ev_magnitude.mag = moment_magnitude
ev_magnitude.magnitude_type = 'Mw'
ev_magnitude.evaluation_mode = 'automatic'
ev.magnitudes.append(ev_magnitude)
# write QuakeML file
cat = Catalog(events=[ev])
memfile = io.BytesIO()
cat.write(memfile, format="quakeml", validate=IS_RECENT_LXML)
memfile.seek(0, 0)
new_cat = _read_quakeml(memfile)
self.assertEqual(len(new_cat), 1)
event = new_cat[0]
self.assertEqual(len(event.origins), 1)
self.assertEqual(len(event.magnitudes), 1)
self.assertEqual(len(event.focal_mechanisms), 1)
org = event.origins[0]
mag = event.magnitudes[0]
fm = event.focal_mechanisms[0]
self.assertEqual(org.latitude, lat)
self.assertEqual(org.longitude, lon)
self.assertEqual(org.depth, depth)
self.assertEqual(org.time, org_time)
# Moment tensor.
mt = fm.moment_tensor.tensor
self.assertTrue((fm.moment_tensor.scalar_moment - scalar_moment) /
scalar_moment < scalar_moment * 1E-10)
self.assertEqual(mt.m_rr, mrr)
self.assertEqual(mt.m_pp, mpp)
self.assertEqual(mt.m_tt, mtt)
self.assertEqual(mt.m_rt, mtr)
self.assertEqual(mt.m_rp, mpr)
self.assertEqual(mt.m_tp, mtp)
# Mag
self.assertAlmostEqual(mag.mag, moment_magnitude)
self.assertEqual(mag.magnitude_type, "Mw")
self.assertEqual(mag.evaluation_mode, "automatic")
def par2quakeml(Par_filename,
QuakeML_filename,
rotation_axis=[0.0, 1.0, 0.0],
rotation_angle=-57.5,
origin_time="2000-01-01 00:00:00.0",
event_type="other event"):
# initialise event
ev = Event()
# open and read Par file
fid = open(Par_filename, 'r')
fid.readline()
fid.readline()
fid.readline()
fid.readline()
lat_old = 90.0 - float(fid.readline().strip().split()[0])
lon_old = float(fid.readline().strip().split()[0])
depth = float(fid.readline().strip().split()[0])
fid.readline()
Mtt_old = float(fid.readline().strip().split()[0])
Mpp_old = float(fid.readline().strip().split()[0])
Mrr_old = float(fid.readline().strip().split()[0])
Mtp_old = float(fid.readline().strip().split()[0])
Mtr_old = float(fid.readline().strip().split()[0])
Mpr_old = float(fid.readline().strip().split()[0])
# rotate event into physical domain
lat, lon = rot.rotate_lat_lon(lat_old, lon_old, rotation_axis,
rotation_angle)
Mrr, Mtt, Mpp, Mtr, Mpr, Mtp = rot.rotate_moment_tensor(
Mrr_old, Mtt_old, Mpp_old, Mtr_old, Mpr_old, Mtp_old, lat_old, lon_old,
rotation_axis, rotation_angle)
# populate event origin data
ev.event_type = event_type
ev_origin = Origin()
ev_origin.time = UTCDateTime(origin_time)
ev_origin.latitude = lat
ev_origin.longitude = lon
ev_origin.depth = depth
ev.origins.append(ev_origin)
# populte event moment tensor
ev_tensor = Tensor()
ev_tensor.m_rr = Mrr
ev_tensor.m_tt = Mtt
ev_tensor.m_pp = Mpp
ev_tensor.m_rt = Mtr
ev_tensor.m_rp = Mpr
ev_tensor.m_tp = Mtp
ev_momenttensor = MomentTensor()
ev_momenttensor.tensor = ev_tensor
ev_momenttensor.scalar_moment = np.sqrt(Mrr**2 + Mtt**2 + Mpp**2 + Mtr**2 +
Mpr**2 + Mtp**2)
ev_focalmechanism = FocalMechanism()
ev_focalmechanism.moment_tensor = ev_momenttensor
ev_focalmechanism.nodal_planes = NodalPlanes().setdefault(0, 0)
ev.focal_mechanisms.append(ev_focalmechanism)
# populate event magnitude
ev_magnitude = Magnitude()
ev_magnitude.mag = 0.667 * (np.log10(ev_momenttensor.scalar_moment) - 9.1)
ev_magnitude.magnitude_type = 'Mw'
ev.magnitudes.append(ev_magnitude)
# write QuakeML file
cat = Catalog()
cat.append(ev)
cat.write(QuakeML_filename, format="quakeml")
# clean up
fid.close()
def _parseRecordDp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._intZero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + '.' + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == 'FX':
orig_time_stderr = 'Fixed'
else:
orig_time_stderr =\
self._floatWithFormat(orig_time_stderr, '2.1', scale)
centroid_latitude = self._floatWithFormat(line[17:21], '4.2')
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinateSign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == 'FX':
lat_stderr = 'Fixed'
else:
lat_stderr = self._floatWithFormat(lat_stderr, '3.2', scale)
centroid_longitude = self._floatWithFormat(line[25:30], '5.2')
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinateSign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == 'FX':
lon_stderr = 'Fixed'
else:
lon_stderr = self._floatWithFormat(lon_stderr, '3.2', scale)
centroid_depth = self._floatWithFormat(line[34:38], '4.1')
depth_stderr = line[38:40]
if depth_stderr == 'FX' or depth_stderr == 'BD':
depth_stderr = 'Fixed'
else:
depth_stderr = self._floatWithFormat(depth_stderr, '2.1', scale)
station_number = self._intZero(line[40:43])
component_number = self._intZero(line[43:46])
station_number2 = self._intZero(line[46:48])
component_number2 = self._intZero(line[48:51])
#unused: half_duration = self._floatWithFormat(line[51:54], '3.1')
moment = self._floatWithFormat(line[54:56], '2.1')
moment_stderr = self._floatWithFormat(line[56:58], '2.1')
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split('/')[-1]
#Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != '.':
origin = Origin()
res_id = '/'.join(
(res_id_prefix, 'origin', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info =\
CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime('%Y%m%d')
origin.time = UTCDateTime(date + centroid_origin_time)
#Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._storeUncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == 'Fixed' and lon_stderr == 'Fixed':
origin.epicenter_fixed = True
else:
self._storeUncertainty(origin.latitude_errors,
self._latErrToDeg(lat_stderr))
self._storeUncertainty(
origin.longitude_errors,
self._lonErrToDeg(lon_stderr, origin.latitude))
if depth_stderr == 'Fixed':
origin.depth_type = 'operator assigned'
else:
origin.depth_type = 'from location'
self._storeUncertainty(origin.depth_errors,
depth_stderr,
scale=1000)
quality = OriginQuality()
quality.used_station_count =\
station_number + station_number2
quality.used_phase_count =\
component_number + component_number2
origin.quality = quality
origin.type = 'centroid'
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = '/'.join(
(res_id_prefix, 'focalmechanism', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info =\
CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
#this is required for QuakeML validation:
res_id = '/'.join((res_id_prefix, 'no-origin'))
moment_tensor.derived_origin_id =\
ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = '/'.join(
(res_id_prefix, 'momenttensor', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._storeUncertainty(moment_tensor.scalar_moment_errors,
moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == 'C':
res_id = '/'.join((res_id_prefix, 'methodID=CMT'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#CMT algorithm uses long-period body waves,
#very-long-period surface waves and
#intermediate period surface waves (since 2004
#for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = 'combined'
if computation_type == 'M':
res_id = '/'.join((res_id_prefix, 'methodID=moment_tensor'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: not sure which kind of data is used by
#"moment tensor" algorithm.
data_used.wave_type = 'unknown'
elif computation_type == 'B':
res_id = '/'.join((res_id_prefix, 'methodID=broadband_data'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: is 'combined' correct here?
data_used.wave_type = 'combined'
elif computation_type == 'F':
res_id = '/'.join((res_id_prefix, 'methodID=P-wave_first_motion'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = 'P waves'
elif computation_type == 'S':
res_id = '/'.join((res_id_prefix, 'methodID=scalar_moment'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: not sure which kind of data is used
#for scalar moment determination.
data_used.wave_type = 'unknown'
moment_tensor.data_used = data_used
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def _parse_record_dp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._int_zero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + '.' + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == 'FX':
orig_time_stderr = 'Fixed'
else:
orig_time_stderr = \
self._float_with_format(orig_time_stderr, '2.1', scale)
centroid_latitude = self._float_with_format(line[17:21], '4.2')
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinate_sign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == 'FX':
lat_stderr = 'Fixed'
else:
lat_stderr = self._float_with_format(lat_stderr, '3.2', scale)
centroid_longitude = self._float_with_format(line[25:30], '5.2')
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinate_sign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == 'FX':
lon_stderr = 'Fixed'
else:
lon_stderr = self._float_with_format(lon_stderr, '3.2', scale)
centroid_depth = self._float_with_format(line[34:38], '4.1')
depth_stderr = line[38:40]
if depth_stderr == 'FX' or depth_stderr == 'BD':
depth_stderr = 'Fixed'
else:
depth_stderr = self._float_with_format(depth_stderr, '2.1', scale)
station_number = self._int_zero(line[40:43])
component_number = self._int_zero(line[43:46])
station_number2 = self._int_zero(line[46:48])
component_number2 = self._int_zero(line[48:51])
# unused: half_duration = self._float_with_format(line[51:54], '3.1')
moment = self._float_with_format(line[54:56], '2.1')
moment_stderr = self._float_with_format(line[56:58], '2.1')
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split('/')[-1]
# Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != '.':
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = \
CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime('%Y%m%d')
origin.time = UTCDateTime(date + centroid_origin_time)
# Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._store_uncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == 'Fixed' and lon_stderr == 'Fixed':
origin.epicenter_fixed = True
else:
self._store_uncertainty(origin.latitude_errors,
self._lat_err_to_deg(lat_stderr))
self._store_uncertainty(origin.longitude_errors,
self._lon_err_to_deg(lon_stderr,
origin.latitude))
if depth_stderr == 'Fixed':
origin.depth_type = 'operator assigned'
else:
origin.depth_type = 'from location'
self._store_uncertainty(origin.depth_errors,
depth_stderr, scale=1000)
quality = OriginQuality()
quality.used_station_count = \
station_number + station_number2
quality.used_phase_count = \
component_number + component_number2
origin.quality = quality
origin.origin_type = 'centroid'
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = '/'.join((res_id_prefix, 'focalmechanism',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info = \
CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
# this is required for QuakeML validation:
res_id = '/'.join((res_id_prefix, 'no-origin'))
moment_tensor.derived_origin_id = \
ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = '/'.join((res_id_prefix, 'momenttensor',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._store_uncertainty(moment_tensor.scalar_moment_errors,
moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == 'C':
res_id = '/'.join((res_id_prefix, 'methodID=CMT'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# CMT algorithm uses long-period body waves,
# very-long-period surface waves and
# intermediate period surface waves (since 2004
# for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = 'combined'
if computation_type == 'M':
res_id = '/'.join((res_id_prefix, 'methodID=moment_tensor'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used by
# "moment tensor" algorithm.
data_used.wave_type = 'unknown'
elif computation_type == 'B':
res_id = '/'.join((res_id_prefix, 'methodID=broadband_data'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: is 'combined' correct here?
data_used.wave_type = 'combined'
elif computation_type == 'F':
res_id = '/'.join((res_id_prefix, 'methodID=P-wave_first_motion'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = 'P waves'
elif computation_type == 'S':
res_id = '/'.join((res_id_prefix, 'methodID=scalar_moment'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used
# for scalar moment determination.
data_used.wave_type = 'unknown'
moment_tensor.data_used = [data_used]
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def par2quakeml(Par_filename, QuakeML_filename, rotation_axis=[0.0, 1.0, 0.0],
rotation_angle=-57.5, origin_time="2000-01-01 00:00:00.0",
event_type="other event"):
# initialise event
ev = Event()
# open and read Par file
fid = open(Par_filename, 'r')
fid.readline()
fid.readline()
fid.readline()
fid.readline()
lat_old = 90.0 - float(fid.readline().strip().split()[0])
lon_old = float(fid.readline().strip().split()[0])
depth = float(fid.readline().strip().split()[0])
fid.readline()
Mtt_old = float(fid.readline().strip().split()[0])
Mpp_old = float(fid.readline().strip().split()[0])
Mrr_old = float(fid.readline().strip().split()[0])
Mtp_old = float(fid.readline().strip().split()[0])
Mtr_old = float(fid.readline().strip().split()[0])
Mpr_old = float(fid.readline().strip().split()[0])
# rotate event into physical domain
lat, lon = rot.rotate_lat_lon(lat_old, lon_old, rotation_axis,
rotation_angle)
Mrr, Mtt, Mpp, Mtr, Mpr, Mtp = rot.rotate_moment_tensor(
Mrr_old, Mtt_old, Mpp_old, Mtr_old, Mpr_old, Mtp_old, lat_old, lon_old,
rotation_axis, rotation_angle)
# populate event origin data
ev.event_type = event_type
ev_origin = Origin()
ev_origin.time = UTCDateTime(origin_time)
ev_origin.latitude = lat
ev_origin.longitude = lon
ev_origin.depth = depth
ev.origins.append(ev_origin)
# populte event moment tensor
ev_tensor = Tensor()
ev_tensor.m_rr = Mrr
ev_tensor.m_tt = Mtt
ev_tensor.m_pp = Mpp
ev_tensor.m_rt = Mtr
ev_tensor.m_rp = Mpr
ev_tensor.m_tp = Mtp
ev_momenttensor = MomentTensor()
ev_momenttensor.tensor = ev_tensor
ev_momenttensor.scalar_moment = np.sqrt(Mrr ** 2 + Mtt ** 2 + Mpp ** 2 +
Mtr ** 2 + Mpr ** 2 + Mtp ** 2)
ev_focalmechanism = FocalMechanism()
ev_focalmechanism.moment_tensor = ev_momenttensor
ev_focalmechanism.nodal_planes = NodalPlanes().setdefault(0, 0)
ev.focal_mechanisms.append(ev_focalmechanism)
# populate event magnitude
ev_magnitude = Magnitude()
ev_magnitude.mag = 0.667 * (np.log10(ev_momenttensor.scalar_moment) - 9.1)
ev_magnitude.magnitude_type = 'Mw'
ev.magnitudes.append(ev_magnitude)
# write QuakeML file
cat = Catalog()
cat.append(ev)
cat.write(QuakeML_filename, format="quakeml")
# clean up
fid.close()
def build(self):
"""
Build an obspy moment tensor focal mech event
This makes the tensor output into an Event containing:
1) a FocalMechanism with a MomentTensor, NodalPlanes, and PrincipalAxes
2) a Magnitude of the Mw from the Tensor
Which is what we want for outputting QuakeML using
the (slightly modified) obspy code.
Input
-----
filehandle => open file OR str from filehandle.read()
Output
------
event => instance of Event() class as described above
"""
p = self.parser
event = Event(event_type='earthquake')
origin = Origin()
focal_mech = FocalMechanism()
nodal_planes = NodalPlanes()
moment_tensor = MomentTensor()
principal_ax = PrincipalAxes()
magnitude = Magnitude()
data_used = DataUsed()
creation_info = CreationInfo(agency_id='NN')
ev_mode = 'automatic'
ev_stat = 'preliminary'
evid = None
orid = None
# Parse the entire file line by line.
for n,l in enumerate(p.line):
if 'REVIEWED BY NSL STAFF' in l:
ev_mode = 'manual'
ev_stat = 'reviewed'
if 'Event ID' in l:
evid = p._id(n)
if 'Origin ID' in l:
orid = p._id(n)
if 'Ichinose' in l:
moment_tensor.category = 'regional'
if re.match(r'^\d{4}\/\d{2}\/\d{2}', l):
ev = p._event_info(n)
if 'Depth' in l:
derived_depth = p._depth(n)
if 'Mw' in l:
magnitude.mag = p._mw(n)
magnitude.magnitude_type = 'Mw'
if 'Mo' in l and 'dyne' in l:
moment_tensor.scalar_moment = p._mo(n)
if 'Percent Double Couple' in l:
moment_tensor.double_couple = p._percent(n)
if 'Percent CLVD' in l:
moment_tensor.clvd = p._percent(n)
if 'Epsilon' in l:
moment_tensor.variance = p._epsilon(n)
if 'Percent Variance Reduction' in l:
moment_tensor.variance_reduction = p._percent(n)
if 'Major Double Couple' in l and 'strike' in p.line[n+1]:
np = p._double_couple(n)
nodal_planes.nodal_plane_1 = NodalPlane(*np[0])
nodal_planes.nodal_plane_2 = NodalPlane(*np[1])
nodal_planes.preferred_plane = 1
if 'Spherical Coordinates' in l:
mt = p._mt_sphere(n)
moment_tensor.tensor = Tensor(
m_rr = mt['Mrr'],
m_tt = mt['Mtt'],
m_pp = mt['Mff'],
m_rt = mt['Mrt'],
m_rp = mt['Mrf'],
m_tp = mt['Mtf'],
)
if 'Eigenvalues and eigenvectors of the Major Double Couple' in l:
ax = p._vectors(n)
principal_ax.t_axis = Axis(ax['T']['trend'], ax['T']['plunge'], ax['T']['ev'])
principal_ax.p_axis = Axis(ax['P']['trend'], ax['P']['plunge'], ax['P']['ev'])
principal_ax.n_axis = Axis(ax['N']['trend'], ax['N']['plunge'], ax['N']['ev'])
if 'Number of Stations' in l:
data_used.station_count = p._number_of_stations(n)
if 'Maximum' in l and 'Gap' in l:
focal_mech.azimuthal_gap = p._gap(n)
if re.match(r'^Date', l):
creation_info.creation_time = p._creation_time(n)
# Creation Time
creation_info.version = orid
# Fill in magnitude values
magnitude.evaluation_mode = ev_mode
magnitude.evaluation_status = ev_stat
magnitude.creation_info = creation_info.copy()
magnitude.resource_id = self._rid(magnitude)
# Stub origin
origin.time = ev.get('time')
origin.latitude = ev.get('lat')
origin.longitude = ev.get('lon')
origin.depth = derived_depth * 1000.
origin.depth_type = "from moment tensor inversion"
origin.creation_info = creation_info.copy()
# Unique from true origin ID
_oid = self._rid(origin)
origin.resource_id = ResourceIdentifier(str(_oid) + '/mt')
del _oid
# Make an id for the MT that references this origin
ogid = str(origin.resource_id)
doid = ResourceIdentifier(ogid, referred_object=origin)
# Make an id for the moment tensor mag which references this mag
mrid = str(magnitude.resource_id)
mmid = ResourceIdentifier(mrid, referred_object=magnitude)
# MT todo: could check/use URL for RID if parsing the php file
moment_tensor.evaluation_mode = ev_mode
moment_tensor.evaluation_status = ev_stat
moment_tensor.data_used = data_used
moment_tensor.moment_magnitude_id = mmid
moment_tensor.derived_origin_id = doid
moment_tensor.creation_info = creation_info.copy()
moment_tensor.resource_id = self._rid(moment_tensor)
# Fill in focal_mech values
focal_mech.nodal_planes = nodal_planes
focal_mech.moment_tensor = moment_tensor
focal_mech.principal_axes = principal_ax
focal_mech.creation_info = creation_info.copy()
focal_mech.resource_id = self._rid(focal_mech)
# add mech and new magnitude to event
event.focal_mechanisms = [focal_mech]
event.magnitudes = [magnitude]
event.origins = [origin]
event.creation_info = creation_info.copy()
# If an MT was done, that's the preferred mag/mech
event.preferred_magnitude_id = str(magnitude.resource_id)
event.preferred_focal_mechanism_id = str(focal_mech.resource_id)
if evid:
event.creation_info.version = evid
event.resource_id = self._rid(event)
self.event = event
def _parseRecordDp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._intZero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + "." + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == "FX":
orig_time_stderr = "Fixed"
else:
orig_time_stderr = self._floatWithFormat(orig_time_stderr, "2.1", scale)
centroid_latitude = self._floatWithFormat(line[17:21], "4.2")
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinateSign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == "FX":
lat_stderr = "Fixed"
else:
lat_stderr = self._floatWithFormat(lat_stderr, "3.2", scale)
centroid_longitude = self._floatWithFormat(line[25:30], "5.2")
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinateSign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == "FX":
lon_stderr = "Fixed"
else:
lon_stderr = self._floatWithFormat(lon_stderr, "3.2", scale)
centroid_depth = self._floatWithFormat(line[34:38], "4.1")
depth_stderr = line[38:40]
if depth_stderr == "FX" or depth_stderr == "BD":
depth_stderr = "Fixed"
else:
depth_stderr = self._floatWithFormat(depth_stderr, "2.1", scale)
station_number = self._intZero(line[40:43])
component_number = self._intZero(line[43:46])
station_number2 = self._intZero(line[46:48])
component_number2 = self._intZero(line[48:51])
# unused: half_duration = self._floatWithFormat(line[51:54], '3.1')
moment = self._floatWithFormat(line[54:56], "2.1")
moment_stderr = self._floatWithFormat(line[56:58], "2.1")
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split("/")[-1]
# Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != ".":
origin = Origin()
res_id = "/".join(
(res_id_prefix, "origin", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime("%Y%m%d")
origin.time = UTCDateTime(date + centroid_origin_time)
# Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._storeUncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == "Fixed" and lon_stderr == "Fixed":
origin.epicenter_fixed = True
else:
self._storeUncertainty(origin.latitude_errors, self._latErrToDeg(lat_stderr))
self._storeUncertainty(origin.longitude_errors, self._lonErrToDeg(lon_stderr, origin.latitude))
if depth_stderr == "Fixed":
origin.depth_type = "operator assigned"
else:
origin.depth_type = "from location"
self._storeUncertainty(origin.depth_errors, depth_stderr, scale=1000)
quality = OriginQuality()
quality.used_station_count = station_number + station_number2
quality.used_phase_count = component_number + component_number2
origin.quality = quality
origin.type = "centroid"
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = "/".join(
(res_id_prefix, "focalmechanism", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info = CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
# this is required for QuakeML validation:
res_id = "/".join((res_id_prefix, "no-origin"))
moment_tensor.derived_origin_id = ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = "/".join(
(res_id_prefix, "momenttensor", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._storeUncertainty(moment_tensor.scalar_moment_errors, moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == "C":
res_id = "/".join((res_id_prefix, "methodID=CMT"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# CMT algorithm uses long-period body waves,
# very-long-period surface waves and
# intermediate period surface waves (since 2004
# for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = "combined"
if computation_type == "M":
res_id = "/".join((res_id_prefix, "methodID=moment_tensor"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used by
# "moment tensor" algorithm.
data_used.wave_type = "unknown"
elif computation_type == "B":
res_id = "/".join((res_id_prefix, "methodID=broadband_data"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: is 'combined' correct here?
data_used.wave_type = "combined"
elif computation_type == "F":
res_id = "/".join((res_id_prefix, "methodID=P-wave_first_motion"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = "P waves"
elif computation_type == "S":
res_id = "/".join((res_id_prefix, "methodID=scalar_moment"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used
# for scalar moment determination.
data_used.wave_type = "unknown"
moment_tensor.data_used = data_used
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def write_qml(config, sourcepar):
if not config.options.qml_file:
return
qml_file = config.options.qml_file
cat = read_events(qml_file)
evid = config.hypo.evid
try:
ev = [e for e in cat if evid in str(e.resource_id)][0]
except Exception:
logging.warning('Unable to find evid "{}" in QuakeML file. '
'QuakeML output will not be written.'.format(evid))
origin = ev.preferred_origin()
if origin is None:
origin = ev.origins[0]
origin_id = origin.resource_id
origin_id_strip = origin_id.id.split('/')[-1]
origin_id_strip = origin_id_strip.replace(config.smi_strip_from_origin_id,
'')
# Common parameters
ssp_version = get_versions()['version']
method_id = config.smi_base + '/sourcespec/' + ssp_version
cr_info = CreationInfo()
cr_info.agency_id = config.agency_id
if config.author is None:
author = '{}@{}'.format(getuser(), gethostname())
else:
author = config.author
cr_info.author = author
cr_info.creation_time = UTCDateTime()
means = sourcepar.means_weight
errors = sourcepar.errors_weight
stationpar = sourcepar.station_parameters
# Magnitude
mag = Magnitude()
_id = config.smi_magnitude_template.replace('$SMI_BASE', config.smi_base)
_id = _id.replace('$ORIGIN_ID', origin_id_strip)
mag.resource_id = ResourceIdentifier(id=_id)
mag.method_id = ResourceIdentifier(id=method_id)
mag.origin_id = origin_id
mag.magnitude_type = 'Mw'
mag.mag = means['Mw']
mag_err = QuantityError()
mag_err.uncertainty = errors['Mw']
mag_err.confidence_level = 68.2
mag.mag_errors = mag_err
mag.station_count = len([_s for _s in stationpar.keys()])
mag.evaluation_mode = 'automatic'
mag.creation_info = cr_info
# Seismic moment -- It has to be stored in a MomentTensor object
# which, in turn, is part of a FocalMechanism object
mt = MomentTensor()
_id = config.smi_moment_tensor_template.replace('$SMI_BASE',
config.smi_base)
_id = _id.replace('$ORIGIN_ID', origin_id_strip)
mt.resource_id = ResourceIdentifier(id=_id)
mt.derived_origin_id = origin_id
mt.moment_magnitude_id = mag.resource_id
mt.scalar_moment = means['Mo']
mt_err = QuantityError()
mt_err.lower_uncertainty = errors['Mo'][0]
mt_err.upper_uncertainty = errors['Mo'][1]
mt_err.confidence_level = 68.2
mt.scalar_moment_errors = mt_err
mt.method_id = method_id
mt.creation_info = cr_info
# And here is the FocalMechanism object
fm = FocalMechanism()
_id = config.smi_focal_mechanism_template.replace('$SMI_BASE',
config.smi_base)
_id = _id.replace('$ORIGIN_ID', origin_id_strip)
fm.resource_id = ResourceIdentifier(id=_id)
fm.triggering_origin_id = origin_id
fm.method_id = ResourceIdentifier(id=method_id)
fm.moment_tensor = mt
fm.creation_info = cr_info
ev.focal_mechanisms.append(fm)
# Station magnitudes
for statId in sorted(stationpar.keys()):
par = stationpar[statId]
st_mag = StationMagnitude()
seed_id = statId.split()[0]
_id = config.smi_station_magnitude_template.replace(
'$SMI_MAGNITUDE_TEMPLATE', config.smi_magnitude_template)
_id = _id.replace('$ORIGIN_ID', origin_id_strip)
_id = _id.replace('$SMI_BASE', config.smi_base)
_id = _id.replace('$WAVEFORM_ID', seed_id)
st_mag.resource_id = ResourceIdentifier(id=_id)
st_mag.origin_id = origin_id
st_mag.mag = par['Mw']
st_mag.station_magnitude_type = 'Mw'
st_mag.method_id = mag.method_id
st_mag.creation_info = cr_info
st_mag.waveform_id = WaveformStreamID(seed_string=seed_id)
st_mag.extra = SSPExtra()
st_mag.extra.moment = SSPTag(par['Mo'])
st_mag.extra.corner_frequency = SSPTag(par['fc'])
st_mag.extra.t_star = SSPTag(par['t_star'])
ev.station_magnitudes.append(st_mag)
st_mag_contrib = StationMagnitudeContribution()
st_mag_contrib.station_magnitude_id = st_mag.resource_id
mag.station_magnitude_contributions.append(st_mag_contrib)
ev.magnitudes.append(mag)
# Write other average parameters as custom tags
ev.extra = SSPExtra()
ev.extra.corner_frequency = SSPContainerTag()
ev.extra.corner_frequency.value.value = SSPTag(means['fc'])
ev.extra.corner_frequency.value.lower_uncertainty =\
SSPTag(errors['fc'][0])
ev.extra.corner_frequency.value.upper_uncertainty =\
SSPTag(errors['fc'][1])
ev.extra.corner_frequency.value.confidence_level = SSPTag(68.2)
ev.extra.t_star = SSPContainerTag()
ev.extra.t_star.value.value = SSPTag(means['t_star'])
ev.extra.t_star.value.uncertainty = SSPTag(errors['t_star'])
ev.extra.t_star.value.confidence_level = SSPTag(68.2)
ev.extra.source_radius = SSPContainerTag()
ev.extra.source_radius.value.value = SSPTag(means['ra'])
ev.extra.source_radius.value.lower_uncertainty =\
SSPTag(errors['ra'][0])
ev.extra.source_radius.value.upper_uncertainty =\
SSPTag(errors['ra'][1])
ev.extra.source_radius.value.confidence_level = SSPTag(68.2)
ev.extra.stress_drop = SSPContainerTag()
ev.extra.stress_drop.value.value = SSPTag(means['bsd'])
ev.extra.stress_drop.value.lower_uncertainty =\
SSPTag(errors['bsd'][0])
ev.extra.stress_drop.value.upper_uncertainty =\
SSPTag(errors['bsd'][1])
ev.extra.stress_drop.value.confidence_level = SSPTag(68.2)
if config.set_preferred_magnitude:
ev.preferred_magnitude_id = mag.resource_id.id
qml_file_out = os.path.join(config.options.outdir, evid + '.xml')
ev.write(qml_file_out, format='QUAKEML')
logging.info('QuakeML file written to: ' + qml_file_out)
