def __toFocalMechanism(parser, focmec_el):
"""
"""
global CURRENT_TYPE
focmec = FocalMechanism()
focmec.resource_id = ResourceIdentifier(
prefix="/".join([RESOURCE_ROOT, "focal_mechanism"]))
if CURRENT_TYPE == "obspyck":
focmec.method_id = "%s/focal_mechanism_method/focmec/1" % RESOURCE_ROOT
else:
focmec.method_id = "%s/focal_mechanism_method/%s/1" % (
RESOURCE_ROOT, parser.xpath2obj('program', focmec_el))
if str(focmec.method_id).lower().endswith("none"):
focmec.method_id = None
focmec.station_polarity_count = parser.xpath2obj("stationPolarityCount",
focmec_el, int)
if focmec.station_polarity_count:
focmec.misfit = parser.xpath2obj("stationPolarityErrorCount",
focmec_el, int) / float(
focmec.station_polarity_count)
focmec.nodal_planes = NodalPlanes()
focmec.nodal_planes.nodal_plane_1 = NodalPlane()
nodal_plane = focmec_el.find("nodalPlanes")
if nodal_plane is None or not len(nodal_plane):
return None
n_p = focmec.nodal_planes.nodal_plane_1
# There is always only one nodal plane, called nodalPlane1
n_p.strike, strike_uncertainty = __toFloatQuantity(
parser, focmec_el, "nodalPlanes/nodalPlane1/strike")
n_p.dip, dip_uncertainty = __toFloatQuantity(
parser, focmec_el, "nodalPlanes/nodalPlane1/dip")
n_p.rake, rake_uncertainty = __toFloatQuantity(
parser, focmec_el, "nodalPlanes/nodalPlane1/rake")
if hasattr(strike_uncertainty, "uncertainty"):
n_p.strike_errors.uncertainty = strike_uncertainty["uncertainty"]
if hasattr(dip_uncertainty, "uncertainty"):
n_p.dip_errors.uncertainty = dip_uncertainty["uncertainty"]
if hasattr(rake_uncertainty, "uncertainty"):
n_p.rake_errors.uncertainty = rake_uncertainty["uncertainty"]
solution_count = parser.xpath2obj("possibleSolutionCount", focmec_el, int)
if solution_count:
focmec.comments.append(
Comment(force_resource_id=False,
resource_id=None,
text="Possible Solution Count: %i" % solution_count))
return focmec
def __toFocalMechanism(parser, focmec_el):
"""
"""
global CURRENT_TYPE
focmec = FocalMechanism()
focmec.resource_id = ResourceIdentifier(prefix="/".join([RESOURCE_ROOT, "focal_mechanism"]))
if CURRENT_TYPE == "obspyck":
focmec.method_id = "%s/focal_mechanism_method/focmec/1" % RESOURCE_ROOT
else:
focmec.method_id = "%s/focal_mechanism_method/%s/1" % (RESOURCE_ROOT,
parser.xpath2obj('program', focmec_el))
if str(focmec.method_id).lower().endswith("none"):
focmec.method_id = None
focmec.station_polarity_count = parser.xpath2obj("stationPolarityCount",
focmec_el, int)
if focmec.station_polarity_count:
focmec.misfit = parser.xpath2obj("stationPolarityErrorCount",
focmec_el, int) / float(focmec.station_polarity_count)
focmec.nodal_planes = NodalPlanes()
focmec.nodal_planes.nodal_plane_1 = NodalPlane()
nodal_plane = focmec_el.find("nodalPlanes")
if nodal_plane is None or not len(nodal_plane):
return None
n_p = focmec.nodal_planes.nodal_plane_1
# There is always only one nodal plane, called nodalPlane1
n_p.strike, strike_uncertainty = __toFloatQuantity(parser,
focmec_el, "nodalPlanes/nodalPlane1/strike")
n_p.dip, dip_uncertainty = __toFloatQuantity(parser, focmec_el,
"nodalPlanes/nodalPlane1/dip")
n_p.rake, rake_uncertainty = __toFloatQuantity(parser,
focmec_el, "nodalPlanes/nodalPlane1/rake")
if hasattr(strike_uncertainty, "uncertainty"):
n_p.strike_errors.uncertainty = strike_uncertainty["uncertainty"]
if hasattr(dip_uncertainty, "uncertainty"):
n_p.dip_errors.uncertainty = dip_uncertainty["uncertainty"]
if hasattr(rake_uncertainty, "uncertainty"):
n_p.rake_errors.uncertainty = rake_uncertainty["uncertainty"]
solution_count = parser.xpath2obj("possibleSolutionCount", focmec_el, int)
if solution_count:
focmec.comments.append(Comment(
force_resource_id=False, resource_id=None,
text="Possible Solution Count: %i" % solution_count))
return focmec
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 outputOBSPY(hp, event=None, only_fm_picks=False):
"""
Make an Event which includes the current focal mechanism information from HASH
Use the 'only_fm_picks' flag to only include the picks HASH used for the FocalMechanism.
This flag will replace the 'picks' and 'arrivals' lists of existing events with new ones.
Inputs
-------
hp : hashpy.HashPype instance
event : obspy.core.event.Event
only_fm_picks : bool of whether to overwrite the picks/arrivals lists
Returns
-------
obspy.core.event.Event
Event will be new if no event was input, FocalMech added to existing event
"""
# Returns new (or updates existing) Event with HASH solution
n = hp.npol
if event is None:
event = Event(focal_mechanisms=[], picks=[], origins=[])
origin = Origin(arrivals=[])
origin.time = UTCDateTime(hp.tstamp)
origin.latitude = hp.qlat
origin.longitude = hp.qlon
origin.depth = hp.qdep
origin.creation_info = CreationInfo(version=hp.icusp)
origin.resource_id = ResourceIdentifier('smi:hash/Origin/{0}'.format(
hp.icusp))
for _i in range(n):
p = Pick()
p.creation_info = CreationInfo(version=hp.arid[_i])
p.resource_id = ResourceIdentifier('smi:nsl/Pick/{0}'.format(
p.creation_info.version))
p.waveform_id = WaveformStreamID(network_code=hp.snet[_i],
station_code=hp.sname[_i],
channel_code=hp.scomp[_i])
if hp.p_pol[_i] > 0:
p.polarity = 'positive'
else:
p.polarity = 'negative'
a = Arrival()
a.creation_info = CreationInfo(version=hp.arid[_i])
a.resource_id = ResourceIdentifier('smi:nsl/Arrival/{0}'.format(
p.creation_info.version))
a.azimuth = hp.p_azi_mc[_i, 0]
a.takeoff_angle = 180. - hp.p_the_mc[_i, 0]
a.pick_id = p.resource_id
origin.arrivals.append(a)
event.picks.append(p)
event.origins.append(origin)
event.preferred_origin_id = origin.resource_id.resource_id
else: # just update the changes
origin = event.preferred_origin()
picks = []
arrivals = []
for _i in range(n):
ind = hp.p_index[_i]
a = origin.arrivals[ind]
p = a.pick_id.getReferredObject()
a.takeoff_angle = hp.p_the_mc[_i, 0]
picks.append(p)
arrivals.append(a)
if only_fm_picks:
origin.arrivals = arrivals
event.picks = picks
# Use me double couple calculator and populate planes/axes etc
x = hp._best_quality_index
# Put all the mechanisms into the 'focal_mechanisms' list, mark "best" as preferred
for s in range(hp.nmult):
dc = DoubleCouple([hp.str_avg[s], hp.dip_avg[s], hp.rak_avg[s]])
ax = dc.axis
focal_mech = FocalMechanism()
focal_mech.creation_info = CreationInfo(creation_time=UTCDateTime(),
author=hp.author)
focal_mech.triggering_origin_id = origin.resource_id
focal_mech.resource_id = ResourceIdentifier(
'smi:hash/FocalMechanism/{0}/{1}'.format(hp.icusp, s + 1))
focal_mech.method_id = ResourceIdentifier('HASH')
focal_mech.nodal_planes = NodalPlanes()
focal_mech.nodal_planes.nodal_plane_1 = NodalPlane(*dc.plane1)
focal_mech.nodal_planes.nodal_plane_2 = NodalPlane(*dc.plane2)
focal_mech.principal_axes = PrincipalAxes()
focal_mech.principal_axes.t_axis = Axis(azimuth=ax['T']['azimuth'],
plunge=ax['T']['dip'])
focal_mech.principal_axes.p_axis = Axis(azimuth=ax['P']['azimuth'],
plunge=ax['P']['dip'])
focal_mech.station_polarity_count = n
focal_mech.azimuthal_gap = hp.magap
focal_mech.misfit = hp.mfrac[s]
focal_mech.station_distribution_ratio = hp.stdr[s]
focal_mech.comments.append(
Comment(
hp.qual[s],
resource_id=ResourceIdentifier(
focal_mech.resource_id.resource_id + '/comment/quality')))
#----------------------------------------
event.focal_mechanisms.append(focal_mech)
if s == x:
event.preferred_focal_mechanism_id = focal_mech.resource_id.resource_id
return event
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 outputOBSPY(hp, event=None, only_fm_picks=False):
"""
Make an Event which includes the current focal mechanism information from HASH
Use the 'only_fm_picks' flag to only include the picks HASH used for the FocalMechanism.
This flag will replace the 'picks' and 'arrivals' lists of existing events with new ones.
Inputs
-------
hp : hashpy.HashPype instance
event : obspy.core.event.Event
only_fm_picks : bool of whether to overwrite the picks/arrivals lists
Returns
-------
obspy.core.event.Event
Event will be new if no event was input, FocalMech added to existing event
"""
# Returns new (or updates existing) Event with HASH solution
n = hp.npol
if event is None:
event = Event(focal_mechanisms=[], picks=[], origins=[])
origin = Origin(arrivals=[])
origin.time = UTCDateTime(hp.tstamp)
origin.latitude = hp.qlat
origin.longitude = hp.qlon
origin.depth = hp.qdep
origin.creation_info = CreationInfo(version=hp.icusp)
origin.resource_id = ResourceIdentifier('smi:hash/Origin/{0}'.format(hp.icusp))
for _i in range(n):
p = Pick()
p.creation_info = CreationInfo(version=hp.arid[_i])
p.resource_id = ResourceIdentifier('smi:hash/Pick/{0}'.format(p.creation_info.version))
p.waveform_id = WaveformStreamID(network_code=hp.snet[_i], station_code=hp.sname[_i], channel_code=hp.scomp[_i])
if hp.p_pol[_i] > 0:
p.polarity = 'positive'
else:
p.polarity = 'negative'
a = Arrival()
a.creation_info = CreationInfo(version=hp.arid[_i])
a.resource_id = ResourceIdentifier('smi:hash/Arrival/{0}'.format(p.creation_info.version))
a.azimuth = hp.p_azi_mc[_i,0]
a.takeoff_angle = 180. - hp.p_the_mc[_i,0]
a.pick_id = p.resource_id
origin.arrivals.append(a)
event.picks.append(p)
event.origins.append(origin)
event.preferred_origin_id = str(origin.resource_id)
else: # just update the changes
origin = event.preferred_origin()
picks = []
arrivals = []
for _i in range(n):
ind = hp.p_index[_i]
a = origin.arrivals[ind]
p = a.pick_id.getReferredObject()
a.takeoff_angle = hp.p_the_mc[_i,0]
picks.append(p)
arrivals.append(a)
if only_fm_picks:
origin.arrivals = arrivals
event.picks = picks
# Use me double couple calculator and populate planes/axes etc
x = hp._best_quality_index
# Put all the mechanisms into the 'focal_mechanisms' list, mark "best" as preferred
for s in range(hp.nmult):
dc = DoubleCouple([hp.str_avg[s], hp.dip_avg[s], hp.rak_avg[s]])
ax = dc.axis
focal_mech = FocalMechanism()
focal_mech.creation_info = CreationInfo(creation_time=UTCDateTime(), author=hp.author)
focal_mech.triggering_origin_id = origin.resource_id
focal_mech.resource_id = ResourceIdentifier('smi:hash/FocalMechanism/{0}/{1}'.format(hp.icusp, s+1))
focal_mech.method_id = ResourceIdentifier('HASH')
focal_mech.nodal_planes = NodalPlanes()
focal_mech.nodal_planes.nodal_plane_1 = NodalPlane(*dc.plane1)
focal_mech.nodal_planes.nodal_plane_2 = NodalPlane(*dc.plane2)
focal_mech.principal_axes = PrincipalAxes()
focal_mech.principal_axes.t_axis = Axis(azimuth=ax['T']['azimuth'], plunge=ax['T']['dip'])
focal_mech.principal_axes.p_axis = Axis(azimuth=ax['P']['azimuth'], plunge=ax['P']['dip'])
focal_mech.station_polarity_count = n
focal_mech.azimuthal_gap = hp.magap
focal_mech.misfit = hp.mfrac[s]
focal_mech.station_distribution_ratio = hp.stdr[s]
focal_mech.comments.append(
Comment(hp.qual[s], resource_id=ResourceIdentifier(str(focal_mech.resource_id) + '/comment/quality'))
)
#----------------------------------------
event.focal_mechanisms.append(focal_mech)
if s == x:
event.preferred_focal_mechanism_id = str(focal_mech.resource_id)
return 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)