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)