def _parseRecordDa(self, line, focal_mechanism):
"""
Parses the 'source parameter data - principal axes and
nodal planes' record Da
"""
exponent = self._intZero(line[3:5])
scale = math.pow(10, exponent)
t_axis_len = self._floatWithFormat(line[5:9], '4.2', scale)
t_axis_stderr = self._floatWithFormat(line[9:12], '3.2', scale)
t_axis_plunge = self._int(line[12:14])
t_axis_azimuth = self._int(line[14:17])
n_axis_len = self._floatWithFormat(line[17:21], '4.2', scale)
n_axis_stderr = self._floatWithFormat(line[21:24], '3.2', scale)
n_axis_plunge = self._int(line[24:26])
n_axis_azimuth = self._int(line[26:29])
p_axis_len = self._floatWithFormat(line[29:33], '4.2', scale)
p_axis_stderr = self._floatWithFormat(line[33:36], '3.2', scale)
p_axis_plunge = self._int(line[36:38])
p_axis_azimuth = self._int(line[38:41])
np1_strike = self._int(line[42:45])
np1_dip = self._int(line[45:47])
np1_slip = self._int(line[47:51])
np2_strike = self._int(line[51:54])
np2_dip = self._int(line[54:56])
np2_slip = self._int(line[56:60])
t_axis = Axis()
t_axis.length = t_axis_len
self._storeUncertainty(t_axis.length_errors, t_axis_stderr)
t_axis.plunge = t_axis_plunge
t_axis.azimuth = t_axis_azimuth
n_axis = Axis()
n_axis.length = n_axis_len
self._storeUncertainty(n_axis.length_errors, n_axis_stderr)
n_axis.plunge = n_axis_plunge
n_axis.azimuth = n_axis_azimuth
p_axis = Axis()
p_axis.length = p_axis_len
self._storeUncertainty(p_axis.length_errors, p_axis_stderr)
p_axis.plunge = p_axis_plunge
p_axis.azimuth = p_axis_azimuth
principal_axes = PrincipalAxes()
principal_axes.t_axis = t_axis
principal_axes.n_axis = n_axis
principal_axes.p_axis = p_axis
focal_mechanism.principal_axes = principal_axes
nodal_plane_1 = NodalPlane()
nodal_plane_1.strike = np1_strike
nodal_plane_1.dip = np1_dip
nodal_plane_1.rake = np1_slip
nodal_plane_2 = NodalPlane()
nodal_plane_2.strike = np2_strike
nodal_plane_2.dip = np2_dip
nodal_plane_2.rake = np2_slip
nodal_planes = NodalPlanes()
nodal_planes.nodal_plane_1 = nodal_plane_1
nodal_planes.nodal_plane_2 = nodal_plane_2
focal_mechanism.nodal_planes = nodal_planes
def _parse_record_da(self, line, focal_mechanism):
"""
Parses the 'source parameter data - principal axes and
nodal planes' record Da
"""
exponent = self._int_zero(line[3:5])
scale = math.pow(10, exponent)
t_axis_len = self._float_with_format(line[5:9], '4.2', scale)
t_axis_stderr = self._float_with_format(line[9:12], '3.2', scale)
t_axis_plunge = self._int(line[12:14])
t_axis_azimuth = self._int(line[14:17])
n_axis_len = self._float_with_format(line[17:21], '4.2', scale)
n_axis_stderr = self._float_with_format(line[21:24], '3.2', scale)
n_axis_plunge = self._int(line[24:26])
n_axis_azimuth = self._int(line[26:29])
p_axis_len = self._float_with_format(line[29:33], '4.2', scale)
p_axis_stderr = self._float_with_format(line[33:36], '3.2', scale)
p_axis_plunge = self._int(line[36:38])
p_axis_azimuth = self._int(line[38:41])
np1_strike = self._int(line[42:45])
np1_dip = self._int(line[45:47])
np1_slip = self._int(line[47:51])
np2_strike = self._int(line[51:54])
np2_dip = self._int(line[54:56])
np2_slip = self._int(line[56:60])
t_axis = Axis()
t_axis.length = t_axis_len
self._store_uncertainty(t_axis.length_errors, t_axis_stderr)
t_axis.plunge = t_axis_plunge
t_axis.azimuth = t_axis_azimuth
n_axis = Axis()
n_axis.length = n_axis_len
self._store_uncertainty(n_axis.length_errors, n_axis_stderr)
n_axis.plunge = n_axis_plunge
n_axis.azimuth = n_axis_azimuth
p_axis = Axis()
p_axis.length = p_axis_len
self._store_uncertainty(p_axis.length_errors, p_axis_stderr)
p_axis.plunge = p_axis_plunge
p_axis.azimuth = p_axis_azimuth
principal_axes = PrincipalAxes()
principal_axes.t_axis = t_axis
principal_axes.n_axis = n_axis
principal_axes.p_axis = p_axis
focal_mechanism.principal_axes = principal_axes
nodal_plane_1 = NodalPlane()
nodal_plane_1.strike = np1_strike
nodal_plane_1.dip = np1_dip
nodal_plane_1.rake = np1_slip
nodal_plane_2 = NodalPlane()
nodal_plane_2.strike = np2_strike
nodal_plane_2.dip = np2_dip
nodal_plane_2.rake = np2_slip
nodal_planes = NodalPlanes()
nodal_planes.nodal_plane_1 = nodal_plane_1
nodal_planes.nodal_plane_2 = nodal_plane_2
focal_mechanism.nodal_planes = nodal_planes
def _map_fplane2focalmech(self, db):
"""
Return an obspy FocalMechanism from an dict of CSS key/values
corresponding to one record. See the 'Join' section for the implied
database join expected.
Inputs
======
db : dict of key/values of CSS fields from the 'fplane' table
Returns
=======
obspy.core.event.FocalMechanism
Notes
=====
Any object that supports the dict 'get' method can be passed as
input, e.g. OrderedDict, custom classes, etc.
"""
#
# NOTE: Antelope schema for this is wrong, no nulls defined
#
fm = FocalMechanism()
nps = NodalPlanes()
nps.nodal_plane_1 = NodalPlane(db.get('str1'), db.get('dip1'), db.get('rake1'))
nps.nodal_plane_2 = NodalPlane(db.get('str2'), db.get('dip2'), db.get('rake2'))
nps.preferred_plane = 1
prin_ax = PrincipalAxes()
prin_ax.t_axis = Axis(db.get('taxazm'),db.get('taxplg'))
prin_ax.p_axis = Axis(db.get('paxazm'),db.get('paxplg'))
fm.nodal_planes = nps
fm.principal_axes = prin_ax
author_string = ':'.join([db['algorithm'], db['auth']])
fm.creation_info = CreationInfo(
version = db.get('mechid'),
creation_time = UTCDateTime(db['lddate']),
agency_id = self.agency,
author = author_string,
)
fm.resource_id = self._rid(fm)
return fm
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
