def attach_new_origin(
old_event: Event,
new_event: Event,
new_origin: Origin,
preferred: bool,
index: Optional[int] = None,
) -> Catalog:
"""
Attach a new origin to an existing events object.
Parameters
----------
old_event : obspy.core.event.Event
The old event that will receive the new origin
new_event : obspy.core.event.Event
The new event that contains the origin, needed for merging picks
that may not exist in old_event
new_origin : obspy.core.event.Origin
The new origin that will be attached to old_event
preferred : bool
If True mark the new origin as the preferred_origin
index : int or None
The origin index of old_cat that new_origin will overwrite, if None
append the new_origin to old_cat.origins
Returns
-------
obspy.Catalog
modifies old_cat in-place, returns old_catalog
"""
# make sure all the picks/amplitudes in new_event are also in old_event
merge_events(old_event, new_event, delete_old=False)
# point the arrivals in the new origin at the old picks
_associate_picks(old_event, new_event, new_origin)
# append the origin
if index is not None: # if this origin is to replace another
try:
old_ori = old_event.origins[index]
except IndexError:
msg = ("%d is not valid for an origin list of length %d") % (
index,
len(old_event.origins),
)
msg += " appending new origin to end of list"
warnings.warn(msg)
old_event.origins.append(new_origin)
else:
# set resource id and creation info
new_origin.resource_id = old_ori.resource_id
new_origin.creation_info = old_ori.creation_info
old_event.origins[index] = new_origin
else:
old_event.origins.append(new_origin)
# bump origin creation info
bump_creation_version(new_origin)
# set preferred
if preferred:
old_event.preferred_origin_id = new_origin.resource_id
validate_catalog(old_event)
return old_event
def set_preferred_values(event: Event):
""" set the preferred values to the last in the list if they are not
defined """
if not event.preferred_origin_id and len(event.origins):
event.preferred_origin_id = event.origins[-1].resource_id
if not event.preferred_magnitude_id and len(event.magnitudes):
event.preferred_magnitude_id = event.magnitudes[-1].resource_id
if not event.preferred_focal_mechanism_id and len(event.focal_mechanisms):
focal_mech_id = event.focal_mechanisms[-1].resource_id
event.preferred_focal_mechanism_id = focal_mech_id
def _deserialize(self, zmap_str):
catalog = Catalog()
for row in zmap_str.split('\n'):
if len(row) == 0:
continue
origin = Origin()
event = Event(origins=[origin])
event.preferred_origin_id = origin.resource_id.id
# Begin value extraction
columns = row.split('\t', 13)[:13] # ignore extra columns
values = dict(zip(_STD_ZMAP_COLUMNS + _EXT_ZMAP_COLUMNS, columns))
# Extract origin
origin.longitude = self._str2num(values.get('lon'))
origin.latitude = self._str2num(values.get('lat'))
depth = self._str2num(values.get('depth'))
if depth is not None:
origin.depth = depth * 1000.0
z_err = self._str2num(values.get('z_err'))
if z_err is not None:
origin.depth_errors.uncertainty = z_err * 1000.0
h_err = self._str2num(values.get('h_err'))
if h_err is not None:
ou = OriginUncertainty()
ou.horizontal_uncertainty = h_err
ou.preferred_description = 'horizontal uncertainty'
origin.origin_uncertainty = ou
year = self._str2num(values.get('year'))
if year is not None:
t_fields = ['year', 'month', 'day', 'hour', 'minute', 'second']
comps = [self._str2num(values.get(f)) for f in t_fields]
if year % 1 != 0:
origin.time = self._decyear2utc(year)
elif any(v > 0 for v in comps[1:]):
# no seconds involved
if len(comps) < 6:
utc_args = [int(v) for v in comps if v is not None]
# we also have to handle seconds
else:
utc_args = [
int(v) if v is not None else 0 for v in comps[:-1]
]
# just leave float seconds as is
utc_args.append(comps[-1])
origin.time = UTCDateTime(*utc_args)
mag = self._str2num(values.get('mag'))
# Extract magnitude
if mag is not None:
magnitude = Magnitude(mag=mag)
m_err = self._str2num(values.get('m_err'))
magnitude.mag_errors.uncertainty = m_err
event.magnitudes.append(magnitude)
event.preferred_magnitude_id = magnitude.resource_id.id
event.scope_resource_ids()
catalog.append(event)
return catalog
def _deserialize(self, zmap_str):
catalog = Catalog()
for row in zmap_str.split('\n'):
if len(row) == 0:
continue
origin = Origin()
event = Event(origins=[origin])
event.preferred_origin_id = origin.resource_id.id
# Begin value extraction
columns = row.split('\t', 13)[:13] # ignore extra columns
values = dict(zip(_STD_ZMAP_COLUMNS + _EXT_ZMAP_COLUMNS, columns))
# Extract origin
origin.longitude = self._str2num(values.get('lon'))
origin.latitude = self._str2num(values.get('lat'))
depth = self._str2num(values.get('depth'))
if depth is not None:
origin.depth = depth * 1000.0
z_err = self._str2num(values.get('z_err'))
if z_err is not None:
origin.depth_errors.uncertainty = z_err * 1000.0
h_err = self._str2num(values.get('h_err'))
if h_err is not None:
ou = OriginUncertainty()
ou.horizontal_uncertainty = h_err
ou.preferred_description = 'horizontal uncertainty'
origin.origin_uncertainty = ou
year = self._str2num(values.get('year'))
if year is not None:
t_fields = ['year', 'month', 'day', 'hour', 'minute', 'second']
comps = [self._str2num(values.get(f)) for f in t_fields]
if year % 1 != 0:
origin.time = self._decyear2utc(year)
elif any(v > 0 for v in comps[1:]):
# no seconds involved
if len(comps) < 6:
utc_args = [int(v) for v in comps if v is not None]
# we also have to handle seconds
else:
utc_args = [int(v) if v is not None else 0
for v in comps[:-1]]
# just leave float seconds as is
utc_args.append(comps[-1])
origin.time = UTCDateTime(*utc_args)
mag = self._str2num(values.get('mag'))
# Extract magnitude
if mag is not None:
magnitude = Magnitude(mag=mag)
m_err = self._str2num(values.get('m_err'))
magnitude.mag_errors.uncertainty = m_err
event.magnitudes.append(magnitude)
event.preferred_magnitude_id = magnitude.resource_id.id
event.scope_resource_ids()
catalog.append(event)
return catalog
def ORNL_events_to_cat(ornl_file):
"""Make Catalog from ORNL locations"""
cat = Catalog()
loc_df = pd.read_csv(ornl_file, infer_datetime_format=True)
loc_df = loc_df.set_index('event_datetime')
eid = 0
for dt, row in loc_df.iterrows():
ot = UTCDateTime(dt)
hmc_east = row['x(m)']
hmc_north = row['y(m)']
hmc_elev = row['z(m)']
errX = row['error_x (m)']
errY = row['error_y (m)']
errZ = row['error_z (m)']
rms = row['rms (millisecond)']
converter = SURF_converter()
lon, lat, elev = converter.to_lonlat((hmc_east, hmc_north,
hmc_elev))
o = Origin(time=ot, latitude=lat, longitude=lon, depth=130 - elev)
o.origin_uncertainty = OriginUncertainty()
o.quality = OriginQuality()
ou = o.origin_uncertainty
oq = o.quality
ou.max_horizontal_uncertainty = np.max([errX, errY])
ou.min_horizontal_uncertainty = np.min([errX, errY])
o.depth_errors.uncertainty = errZ
oq.standard_error = rms * 1e3
extra = AttribDict({
'hmc_east': {
'value': hmc_east,
'namespace': 'smi:local/hmc'
},
'hmc_north': {
'value': hmc_north,
'namespace': 'smi:local/hmc'
},
'hmc_elev': {
'value': hmc_elev,
'namespace': 'smi:local/hmc'
},
'hmc_eid': {
'value': eid,
'namespace': 'smi:local/hmc'
}
})
o.extra = extra
rid = ResourceIdentifier(id=ot.strftime('%Y%m%d%H%M%S%f'))
# Dummy magnitude of 1. for all events until further notice
mag = Magnitude(mag=1., mag_errors=QuantityError(uncertainty=1.))
ev = Event(origins=[o], magnitudes=[mag], resource_id=rid)
ev.preferred_origin_id = o.resource_id.id
cat.events.append(ev)
eid += 1
return cat
def read_header_line(string_line):
new_event = Event()
line = string_line
param_event = line.split()[1:]
### check if line as required number of arguments
if len(param_event) != 14:
return new_event
### Get parameters
year, month, day = [int(x) for x in param_event[0:3]]
hour, minu = [int(x) for x in param_event[3:5]]
sec = float(param_event[5])
if sec >= 60:
sec = 59.999
lat, lon, z = [float(x) for x in param_event[6:9]]
mag = float(param_event[9])
errh, errz, rms = [float(x) for x in param_event[10:13]]
_time = UTCDateTime(year, month, day, hour, minu, sec)
_origin_quality = OriginQuality(standard_error=rms)
# change what's next to handle origin with no errors estimates
origin = Origin(time=_time,
longitude=lon,
latitude=lat,
depth=z,
longitude_errors=QuantityError(uncertainty=errh),
latitude_errors=QuantityError(uncertainty=errh),
depth_errors=QuantityError(uncertainty=errz),
quality=_origin_quality)
magnitude = Magnitude(mag=mag, origin_id=origin.resource_id)
### Return
new_event.origins.append(origin)
new_event.magnitudes.append(magnitude)
new_event.preferred_origin_id = origin.resource_id
new_event.preferred_magnitude_id = magnitude.resource_id
return new_event
def _deserialize(self, zmap_str):
catalog = Catalog()
for row in zmap_str.split("\n"):
if len(row) == 0:
continue
origin = Origin()
event = Event(origins=[origin])
event.preferred_origin_id = origin.resource_id.id
# Begin value extraction
columns = row.split("\t", 13)[:13] # ignore extra columns
values = dict(zip(_STD_ZMAP_COLUMNS + _EXT_ZMAP_COLUMNS, columns))
# Extract origin
origin.longitude = self._str2num(values.get("lon"))
origin.latitude = self._str2num(values.get("lat"))
depth = self._str2num(values.get("depth"))
if depth is not None:
origin.depth = depth * 1000.0
z_err = self._str2num(values.get("z_err"))
if z_err is not None:
origin.depth_errors.uncertainty = z_err * 1000.0
h_err = self._str2num(values.get("h_err"))
if h_err is not None:
ou = OriginUncertainty()
ou.horizontal_uncertainty = h_err
ou.preferred_description = "horizontal uncertainty"
origin.origin_uncertainty = ou
year = self._str2num(values.get("year"))
if year is not None:
t_fields = ["year", "month", "day", "hour", "minute", "second"]
comps = [self._str2num(values.get(f)) for f in t_fields]
if year % 1 != 0:
origin.time = self._decyear2utc(year)
elif any(v > 0 for v in comps[1:]):
utc_args = [int(v) for v in comps if v is not None]
origin.time = UTCDateTime(*utc_args)
mag = self._str2num(values.get("mag"))
# Extract magnitude
if mag is not None:
magnitude = Magnitude(mag=mag)
m_err = self._str2num(values.get("m_err"))
magnitude.mag_errors.uncertainty = m_err
event.magnitudes.append(magnitude)
event.preferred_magnitude_id = magnitude.resource_id.id
catalog.append(event)
return catalog
def _parse_event(self, first_line):
"""
Parse an event.
:type first_line: str
:param first_line: First line of an event block, which contains
the event id.
:rtype: :class:`~obspy.core.event.event.Event`
:return: The parsed event or None.
"""
event_id = first_line[5:].strip()
# Skip event without id
if not event_id:
self._warn('Missing event id')
return None
event = Event()
origin, origin_res_id = self._parse_origin(event)
# Skip event without origin
if not origin:
return None
line = self._skip_empty_lines()
self._parse_region_name(line, event)
self._parse_arrivals(event, origin, origin_res_id)
# Origin ResourceIdentifier should be set at the end, when
# Arrivals are already set.
origin.resource_id = origin_res_id
event.origins.append(origin)
event.preferred_origin_id = origin.resource_id.id
# Must be done after the origin parsing
event.creation_info = self._get_creation_info()
public_id = "event/%s" % event_id
event.resource_id = self._get_res_id(public_id)
event.scope_resource_ids()
return event
def _parse_event(self, first_line):
"""
Parse an event.
:type first_line: str
:param first_line: First line of an event block, which contains
the event id.
:rtype: :class:`~obspy.core.event.event.Event`
:return: The parsed event or None.
"""
event_id = first_line[5:].strip()
# Skip event without id
if not event_id:
self._warn('Missing event id')
return None
event = Event()
origin, origin_res_id = self._parse_origin(event)
# Skip event without origin
if not origin:
return None
line = self._skip_empty_lines()
self._parse_region_name(line, event)
self._parse_arrivals(event, origin, origin_res_id)
# Origin ResourceIdentifier should be set at the end, when
# Arrivals are already set.
origin.resource_id = origin_res_id
event.origins.append(origin)
event.preferred_origin_id = origin.resource_id.id
# Must be done after the origin parsing
event.creation_info = self._get_creation_info()
public_id = "event/%s" % event_id
event.resource_id = self._get_res_id(public_id)
event.scope_resource_ids()
return event
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 _read_single_hypocenter(lines, coordinate_converter, original_picks):
"""
Given a list of lines (starting with a 'NLLOC' line and ending with a
'END_NLLOC' line), parse them into an Event.
"""
try:
# some paranoid checks..
assert lines[0].startswith("NLLOC ")
assert lines[-1].startswith("END_NLLOC")
for line in lines[1:-1]:
assert not line.startswith("NLLOC ")
assert not line.startswith("END_NLLOC")
except Exception:
msg = ("This should not have happened, please report this as a bug at "
"https://github.com/obspy/obspy/issues.")
raise Exception(msg)
indices_phases = [None, None]
for i, line in enumerate(lines):
if line.startswith("PHASE "):
indices_phases[0] = i
elif line.startswith("END_PHASE"):
indices_phases[1] = i
# extract PHASES lines (if any)
if any(indices_phases):
if not all(indices_phases):
msg = ("NLLOC HYP file seems corrupt, 'PHASE' block is corrupt.")
raise RuntimeError(msg)
i1, i2 = indices_phases
lines, phases_lines = lines[:i1] + lines[i2 + 1:], lines[i1 + 1:i2]
else:
phases_lines = []
lines = dict([line.split(None, 1) for line in lines[:-1]])
line = lines["SIGNATURE"]
line = line.rstrip().split('"')[1]
signature, version, date, time = line.rsplit(" ", 3)
# new NLLoc > 6.0 seems to add prefix 'run:' before date
if date.startswith('run:'):
date = date[4:]
signature = signature.strip()
creation_time = UTCDateTime.strptime(date + time, str("%d%b%Y%Hh%Mm%S"))
if coordinate_converter:
# maximum likelihood origin location in km info line
line = lines["HYPOCENTER"]
x, y, z = coordinate_converter(*map(float, line.split()[1:7:2]))
else:
# maximum likelihood origin location lon lat info line
line = lines["GEOGRAPHIC"]
y, x, z = map(float, line.split()[8:13:2])
# maximum likelihood origin time info line
line = lines["GEOGRAPHIC"]
year, mon, day, hour, min = map(int, line.split()[1:6])
seconds = float(line.split()[6])
time = UTCDateTime(year, mon, day, hour, min, seconds, strict=False)
# distribution statistics line
line = lines["STATISTICS"]
covariance_xx = float(line.split()[7])
covariance_yy = float(line.split()[13])
covariance_zz = float(line.split()[17])
stats_info_string = str(
"Note: Depth/Latitude/Longitude errors are calculated from covariance "
"matrix as 1D marginal (Lon/Lat errors as great circle degrees) "
"while OriginUncertainty min/max horizontal errors are calculated "
"from 2D error ellipsoid and are therefore seemingly higher compared "
"to 1D errors. Error estimates can be reconstructed from the "
"following original NonLinLoc error statistics line:\nSTATISTICS " +
lines["STATISTICS"])
# goto location quality info line
line = lines["QML_OriginQuality"].split()
(assoc_phase_count, used_phase_count, assoc_station_count,
used_station_count, depth_phase_count) = map(int, line[1:11:2])
stderr, az_gap, sec_az_gap = map(float, line[11:17:2])
gt_level = line[17]
min_dist, max_dist, med_dist = map(float, line[19:25:2])
# goto location quality info line
line = lines["QML_OriginUncertainty"]
if "COMMENT" in lines:
comment = lines["COMMENT"].strip()
comment = comment.strip('\'"')
comment = comment.strip()
hor_unc, min_hor_unc, max_hor_unc, hor_unc_azim = \
map(float, line.split()[1:9:2])
# assign origin info
event = Event()
o = Origin()
event.origins = [o]
event.preferred_origin_id = o.resource_id
o.origin_uncertainty = OriginUncertainty()
o.quality = OriginQuality()
ou = o.origin_uncertainty
oq = o.quality
o.comments.append(Comment(text=stats_info_string, force_resource_id=False))
event.comments.append(Comment(text=comment, force_resource_id=False))
# SIGNATURE field's first item is LOCSIG, which is supposed to be
# 'Identification of an individual, institiution or other entity'
# according to
# http://alomax.free.fr/nlloc/soft6.00/control.html#_NLLoc_locsig_
# so use it as author in creation info
event.creation_info = CreationInfo(creation_time=creation_time,
version=version,
author=signature)
o.creation_info = CreationInfo(creation_time=creation_time,
version=version,
author=signature)
# negative values can appear on diagonal of covariance matrix due to a
# precision problem in NLLoc implementation when location coordinates are
# large compared to the covariances.
o.longitude = x
try:
o.longitude_errors.uncertainty = kilometer2degrees(sqrt(covariance_xx))
except ValueError:
if covariance_xx < 0:
msg = ("Negative value in XX value of covariance matrix, not "
"setting longitude error (epicentral uncertainties will "
"still be set in origin uncertainty).")
warnings.warn(msg)
else:
raise
o.latitude = y
try:
o.latitude_errors.uncertainty = kilometer2degrees(sqrt(covariance_yy))
except ValueError:
if covariance_yy < 0:
msg = ("Negative value in YY value of covariance matrix, not "
"setting longitude error (epicentral uncertainties will "
"still be set in origin uncertainty).")
warnings.warn(msg)
else:
raise
o.depth = z * 1e3 # meters!
o.depth_errors.uncertainty = sqrt(covariance_zz) * 1e3 # meters!
o.depth_errors.confidence_level = 68
o.depth_type = str("from location")
o.time = time
ou.horizontal_uncertainty = hor_unc
ou.min_horizontal_uncertainty = min_hor_unc
ou.max_horizontal_uncertainty = max_hor_unc
# values of -1 seem to be used for unset values, set to None
for field in ("horizontal_uncertainty", "min_horizontal_uncertainty",
"max_horizontal_uncertainty"):
if ou.get(field, -1) == -1:
ou[field] = None
else:
ou[field] *= 1e3 # meters!
ou.azimuth_max_horizontal_uncertainty = hor_unc_azim
ou.preferred_description = str("uncertainty ellipse")
ou.confidence_level = 68 # NonLinLoc in general uses 1-sigma (68%) level
oq.standard_error = stderr
oq.azimuthal_gap = az_gap
oq.secondary_azimuthal_gap = sec_az_gap
oq.used_phase_count = used_phase_count
oq.used_station_count = used_station_count
oq.associated_phase_count = assoc_phase_count
oq.associated_station_count = assoc_station_count
oq.depth_phase_count = depth_phase_count
oq.ground_truth_level = gt_level
oq.minimum_distance = kilometer2degrees(min_dist)
oq.maximum_distance = kilometer2degrees(max_dist)
oq.median_distance = kilometer2degrees(med_dist)
# go through all phase info lines
for line in phases_lines:
line = line.split()
arrival = Arrival()
o.arrivals.append(arrival)
station = str(line[0])
phase = str(line[4])
arrival.phase = phase
arrival.distance = kilometer2degrees(float(line[21]))
arrival.azimuth = float(line[23])
arrival.takeoff_angle = float(line[24])
arrival.time_residual = float(line[16])
arrival.time_weight = float(line[17])
pick = Pick()
# network codes are not used by NonLinLoc, so they can not be known
# when reading the .hyp file.. to conform with QuakeML standard set an
# empty network code
wid = WaveformStreamID(network_code="", station_code=station)
# have to split this into ints for overflow to work correctly
date, hourmin, sec = map(str, line[6:9])
ymd = [int(date[:4]), int(date[4:6]), int(date[6:8])]
hm = [int(hourmin[:2]), int(hourmin[2:4])]
t = UTCDateTime(*(ymd + hm), strict=False) + float(sec)
pick.waveform_id = wid
pick.time = t
pick.time_errors.uncertainty = float(line[10])
pick.phase_hint = phase
pick.onset = ONSETS.get(line[3].lower(), None)
pick.polarity = POLARITIES.get(line[5].lower(), None)
# try to determine original pick for each arrival
for pick_ in original_picks:
wid = pick_.waveform_id
if station == wid.station_code and phase == pick_.phase_hint:
pick = pick_
break
else:
# warn if original picks were specified and we could not associate
# the arrival correctly
if original_picks:
msg = ("Could not determine corresponding original pick for "
"arrival. "
"Falling back to pick information in NonLinLoc "
"hypocenter-phase file.")
warnings.warn(msg)
event.picks.append(pick)
arrival.pick_id = pick.resource_id
event.scope_resource_ids()
return event
def _load_events(self):
self._load_events_helper()
cache = {}
notFound = defaultdict(int)
oEvents = []
missingStations = defaultdict(int)
lines = []
for e in tqdm(self.eventList, desc='Rank %d' % (self.rank)):
if (e.preferred_origin and len(e.preferred_origin.arrival_list)):
cullList = []
for a in e.preferred_origin.arrival_list:
if (len(a.net)): continue
seedid = '%s.%s.%s.%s' % (a.net, a.sta, a.loc, a.cha)
newCode = None
if (seedid not in cache):
sc = a.sta
lonlat = self.isc_coords_dict[sc]
if (len(lonlat) == 0):
cullList.append(a)
continue
# end if
r = self.fdsn_inventory.getClosestStation(
lonlat[0], lonlat[1], maxdist=1e3) # 1km
#if(a.sta=='KUM'): print a.net, a.sta, a.loc, a.cha, r
if (not r):
notFound[sc] += 1
else:
c = r[0].split('.')[0]
newCode = c
# end if
if (newCode):
cache[seedid] = newCode
# end if
else:
newCode = cache[seedid]
# end if
if (newCode):
#print a.net, newCode
a.net = newCode
sc = self.fdsn_inventory.t[a.net][a.sta]
if (type(sc) == defaultdict):
cullList.append(a)
continue
# end if
da = gps2dist_azimuth(e.preferred_origin.lat,
e.preferred_origin.lon, sc[1],
sc[0])
dist = kilometers2degrees(da[0] / 1e3)
if (np.fabs(a.distance - dist) > 0.5):
#print ([e.preferred_origin.lon, e.preferred_origin.lat, sc[0], sc[1]])
cullList.append(a)
# end if
# end if
# end for
for c in cullList:
e.preferred_origin.arrival_list.remove(c)
# end if
# Create obspy event object
ci = OCreationInfo(author='GA',
creation_time=UTCDateTime(),
agency_id='GA-iteration-1')
oid = self.get_id()
origin = OOrigin(resource_id=OResourceIdentifier(id=oid),
time=UTCDateTime(e.preferred_origin.utctime),
longitude=e.preferred_origin.lon,
latitude=e.preferred_origin.lat,
depth=e.preferred_origin.depthkm * 1e3,
method_id=OResourceIdentifier(id='unknown'),
earth_model_id=OResourceIdentifier(id='iasp91'),
evaluation_mode='automatic',
creation_info=ci)
magnitude = OMagnitude(
resource_id=OResourceIdentifier(id=self.get_id()),
mag=e.preferred_magnitude.magnitude_value,
magnitude_type=e.preferred_magnitude.magnitude_type,
origin_id=OResourceIdentifier(id=oid),
creation_info=ci)
event = OEvent(
resource_id=OResourceIdentifier(id=str(e.public_id)),
creation_info=ci,
event_type='earthquake')
event.origins = [origin]
event.magnitudes = [magnitude]
event.preferred_magnitude_id = magnitude.resource_id
event.preferred_origin_id = origin.resource_id
# Insert old picks
if (not self.discard_old_picks):
for a in e.preferred_origin.arrival_list:
if (type(self.fdsn_inventory.t[a.net][a.sta]) ==
defaultdict):
missingStations[a.net + '.' + a.sta] += 1
continue
# end if
oldPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(a.utctime),
waveform_id=OWaveformStreamID(network_code=a.net,
station_code=a.sta,
channel_code=a.cha),
methodID=OResourceIdentifier('unknown'),
phase_hint=a.phase,
evaluation_mode='automatic',
creation_info=ci)
oldArr = OArrival(
resource_id=OResourceIdentifier(
id=oldPick.resource_id.id + "#"),
pick_id=oldPick.resource_id,
phase=oldPick.phase_hint,
distance=a.distance,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(oldPick)
event.preferred_origin().arrivals.append(oldArr)
# polulate list for text output
line = [
str(e.public_id), '{:<25s}',
e.preferred_origin.utctime.timestamp, '{:f}',
e.preferred_magnitude.magnitude_value, '{:f}',
e.preferred_origin.lon, '{:f}', e.preferred_origin.lat,
'{:f}', e.preferred_origin.depthkm, '{:f}', a.net,
'{:<5s}', a.sta, '{:<5s}', a.cha, '{:<5s}',
a.utctime.timestamp, '{:f}', a.phase, '{:<5s}',
self.fdsn_inventory.t[a.net][a.sta][0], '{:f}',
self.fdsn_inventory.t[a.net][a.sta][1], '{:f}', -999,
'{:f}', -999, '{:f}', a.distance, '{:f}', -999, '{:f}',
-999, '{:f}', -999, '{:f}', -999, '{:f}', -999, '{:f}',
-999, '{:d}', -999, '{:d}'
]
lines.append(line)
# end for
# end if
# Insert our picks
opList = self.our_picks.picks[e.public_id]
if (len(opList)):
for op in opList:
if (type(self.fdsn_inventory.t[op[1]][op[2]]) ==
defaultdict):
missingStations[op[1] + '.' + op[2]] += 1
continue
# end if
newPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(op[0]),
waveform_id=OWaveformStreamID(network_code=op[1],
station_code=op[2],
channel_code=op[3]),
methodID=OResourceIdentifier('phasepapy/aicd'),
backazimuth=op[-1],
phase_hint=op[4],
evaluation_mode='automatic',
comments=[
OComment(
text='phasepapy_snr = ' + str(op[6][0]) +
', quality_measure_cwt = ' + str(op[6][1]) +
', dom_freq = ' + str(op[6][2]) +
', quality_measure_slope = ' + str(op[6][3]) +
', band_index = ' + str(op[6][4]) +
', nsigma = ' + str(op[6][5]),
force_resource_id=False)
],
creation_info=ci)
newArr = OArrival(
resource_id=OResourceIdentifier(
id=newPick.resource_id.id + "#"),
pick_id=newPick.resource_id,
phase=newPick.phase_hint,
azimuth=op[-2],
distance=op[-3],
time_residual=op[5],
time_weight=1.,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(newPick)
event.preferred_origin().arrivals.append(newArr)
# polulate list for text output
line = [
str(e.public_id), '{:<25s}',
e.preferred_origin.utctime.timestamp, '{:f}',
e.preferred_magnitude.magnitude_value, '{:f}',
e.preferred_origin.lon, '{:f}', e.preferred_origin.lat,
'{:f}', e.preferred_origin.depthkm, '{:f}', op[1],
'{:<5s}', op[2], '{:<5s}', op[3], '{:<5s}',
UTCDateTime(op[0]).timestamp, '{:f}', op[4], '{:<5s}',
op[10], '{:f}', op[9], '{:f}', op[12], '{:f}', op[13],
'{:f}', op[11], '{:f}', op[5], '{:f}', op[6][0],
'{:f}', op[6][1], '{:f}', op[6][2], '{:f}', op[6][3],
'{:f}',
int(op[6][4]), '{:d}',
int(op[6][5]), '{:d}'
]
lines.append(line)
# end for
# end if
quality= OOriginQuality(associated_phase_count= len(e.preferred_origin.arrival_list) * \
int(self.discard_old_picks) + \
len(self.our_picks.picks[e.public_id]),
used_phase_count=len(e.preferred_origin.arrival_list) * \
int(self.discard_old_picks) + \
len(self.our_picks.picks[e.public_id]))
event.preferred_origin().quality = quality
if (len(self.our_picks.picks[e.public_id]) == 0
and self.discard_old_picks):
continue
# end if
oEvents.append(event)
# end for // loop over e
if (len(missingStations)):
for k, v in missingStations.items():
self.logger.warning('Missing station %s: %d picks' % (k, v))
# end for
# end if
# write xml output
if (len(oEvents)):
cat = OCatalog(events=oEvents)
ofn = self.output_path + '/%d.xml' % (self.rank)
cat.write(ofn, format='SC3ML')
# end if
# write text output
procfile = open('%s/proc.%d.txt' % (self.output_path, self.rank), 'w+')
for line in lines:
lineout = ' '.join(line[1::2]).format(*line[::2])
procfile.write(lineout + '\n')
# end for
procfile.close()
# combine text output
header = '#eventID originTimestamp mag originLon originLat originDepthKm net sta cha pickTimestamp phase stationLon stationLat az baz distance ttResidual snr qualityMeasureCWT domFreq qualityMeasureSlope bandIndex nSigma\n'
self.comm.barrier()
if (self.rank == 0):
of = open('%s/ensemble.txt' % (self.output_path), 'w+')
of.write(header)
for i in range(self.nproc):
fn = '%s/proc.%d.txt' % (self.output_path, i)
lines = open(fn, 'r').readlines()
for line in lines:
of.write(line)
# end for
if (os.path.exists(fn)): os.remove(fn)
# end for
of.close()
def __read_single_fnetmt_entry(line, **kwargs):
"""
Reads a single F-net moment tensor solution to a
:class:`~obspy.core.event.Event` object.
:param line: String containing moment tensor information.
:type line: str.
"""
a = line.split()
try:
ot = UTCDateTime().strptime(a[0], '%Y/%m/%d,%H:%M:%S.%f')
except ValueError:
ot = UTCDateTime().strptime(a[0], '%Y/%m/%d,%H:%M:%S')
lat, lon, depjma, magjma = map(float, a[1:5])
depjma *= 1000
region = a[5]
strike = tuple(map(int, a[6].split(';')))
dip = tuple(map(int, a[7].split(';')))
rake = tuple(map(int, a[8].split(';')))
mo = float(a[9])
depmt = float(a[10]) * 1000
magmt = float(a[11])
var_red = float(a[12])
mxx, mxy, mxz, myy, myz, mzz, unit = map(float, a[13:20])
event_name = util.gen_sc3_id(ot)
e = Event(event_type="earthquake")
e.resource_id = _get_resource_id(event_name, 'event')
# Standard JMA solution
o_jma = Origin(time=ot, latitude=lat, longitude=lon,
depth=depjma, depth_type="from location",
region=region)
o_jma.resource_id = _get_resource_id(event_name,
'origin', 'JMA')
m_jma = Magnitude(mag=magjma, magnitude_type='ML',
origin_id=o_jma.resource_id)
m_jma.resource_id = _get_resource_id(event_name,
'magnitude', 'JMA')
# MT solution
o_mt = Origin(time=ot, latitude=lat, longitude=lon,
depth=depmt, region=region,
depth_type="from moment tensor inversion")
o_mt.resource_id = _get_resource_id(event_name,
'origin', 'MT')
m_mt = Magnitude(mag=magmt, magnitude_type='Mw',
origin_id=o_mt.resource_id)
m_mt.resource_id = _get_resource_id(event_name,
'magnitude', 'MT')
foc_mec = FocalMechanism(triggering_origin_id=o_jma.resource_id)
foc_mec.resource_id = _get_resource_id(event_name,
"focal_mechanism")
nod1 = NodalPlane(strike=strike[0], dip=dip[0], rake=rake[0])
nod2 = NodalPlane(strike=strike[1], dip=dip[1], rake=rake[1])
nod = NodalPlanes(nodal_plane_1=nod1, nodal_plane_2=nod2)
foc_mec.nodal_planes = nod
tensor = Tensor(m_rr=mxx, m_tt=myy, m_pp=mzz, m_rt=mxy, m_rp=mxz, m_tp=myz)
cm = Comment(text="Basis system: North,East,Down (Jost and \
Herrmann 1989")
cm.resource_id = _get_resource_id(event_name, 'comment', 'mt')
mt = MomentTensor(derived_origin_id=o_mt.resource_id,
moment_magnitude_id=m_mt.resource_id,
scalar_moment=mo, comments=[cm],
tensor=tensor, variance_reduction=var_red)
mt.resource_id = _get_resource_id(event_name,
'moment_tensor')
foc_mec.moment_tensor = mt
e.origins = [o_jma, o_mt]
e.magnitudes = [m_jma, m_mt]
e.focal_mechanisms = [foc_mec]
e.preferred_magnitude_id = m_mt.resource_id.id
e.preferred_origin_id = o_mt.resource_id.id
e.preferred_focal_mechanism_id = foc_mec.resource_id.id
return e
def _dbs_associator(start_time,
end_time,
moving_window,
tbl,
pair_n,
save_dir,
station_list,
consider_combination=False):
if consider_combination == True:
if platform.system() == 'Windows':
Y2000_writer = open(save_dir + "\\" + "Y2000.phs", "w")
else:
Y2000_writer = open(save_dir + "/" + "Y2000.phs", "w")
traceNmae_dic = dict()
st = datetime.strptime(start_time, '%Y-%m-%d %H:%M:%S.%f')
et = datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S.%f')
total_t = et - st
evid = 0
tt = st
pbar = tqdm(total=int(np.ceil(total_t.total_seconds() /
moving_window)),
ncols=100)
while tt < et:
detections = tbl[(tbl.event_start_time >= tt) & (
tbl.event_start_time < tt + timedelta(seconds=moving_window))]
pbar.update()
if len(detections) >= pair_n:
evid += 1
yr = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[0])
mo = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[1])
dy = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[2])
hr = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[0])
mi = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[1])
sec = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[2])
st_lat_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlat']), "Latitude")
st_lon_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlon']), "Longitude")
depth = 5.0
mag = 0.0
# QuakeML
print(detections.iloc[0]['event_start_time'])
if len(detections) / pair_n <= 2:
ch = pair_n
else:
ch = int(len(detections) - pair_n)
picks = []
for ns in range(ch, len(detections) + 1):
comb = 0
for ind in list(combinations(detections.index, ns)):
comb += 1
selected_detections = detections.loc[ind, :]
sorted_detections = selected_detections.sort_values(
'p_arrival_time')
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]),
str(st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
station_buffer = []
row_buffer = []
tr_names = []
tr_names2 = []
for _, row in sorted_detections.iterrows():
trace_name = row['traceID'] + '*' + row[
'station'] + '*' + str(row['event_start_time'])
p_unc = row['p_unc']
p_prob = row['p_prob']
s_unc = row['s_unc']
s_prob = row['s_prob']
if p_unc:
Pweihgt = _weighcalculator_prob(p_prob *
(1 - p_unc))
else:
Pweihgt = _weighcalculator_prob(p_prob)
try:
Pweihgt = int(Pweihgt)
except Exception:
Pweihgt = 4
if s_unc:
Sweihgt = _weighcalculator_prob(s_prob *
(1 - s_unc))
else:
Sweihgt = _weighcalculator_prob(s_prob)
try:
Sweihgt = int(Sweihgt)
except Exception:
Sweihgt = 4
station = "{:<5}".format(row['station'])
network = "{:<2}".format(row['network'])
try:
yrp = "{:>4}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[0])
mop = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[1])
dyp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[0].split('-')[2])
hrp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[0])
mip = "{:>2}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[1])
sec_p = "{:>4}".format(
str(row['p_arrival_time']).split(' ')
[1].split(':')[2])
p = Pick(time=UTCDateTime(
row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="P")
picks.append(p)
except Exception:
sec_p = None
try:
yrs = "{:>4}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[0])
mos = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[1])
dys = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[0].split('-')[2])
hrs = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[0])
mis = "{:>2}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[1])
sec_s = "{:>4}".format(
str(row['s_arrival_time']).split(' ')
[1].split(':')[2])
p = Pick(time=UTCDateTime(
row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="S")
picks.append(p)
except Exception:
sec_s = None
if row['station'] not in station_buffer:
tr_names.append(trace_name)
station_buffer.append(row['station'])
if sec_s:
Y2000_writer.write(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
%
(station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis),
float(0.0), float(sec_s), Sweihgt))
if sec_p:
Y2000_writer.write(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp),
int(mip), float(sec_p), float(0.0)))
else:
tr_names2.append(trace_name)
if sec_s:
row_buffer.append(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
%
(station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), 0.0,
float(sec_s), Sweihgt))
if sec_p:
row_buffer.append(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp),
int(mip), float(sec_p), float(0.0)))
Y2000_writer.write("{:<62}".format(' ') + "%10d" %
(evid) + '\n')
traceNmae_dic[str(evid)] = tr_names
if len(row_buffer) >= 2 * pair_n:
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]), str(
st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
for rr in row_buffer:
Y2000_writer.write(rr)
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names2
tt += timedelta(seconds=moving_window)
# plt.scatter(LTTP, TTP, s=10, marker='o', c='b', alpha=0.4, label='P')
# plt.scatter(LTTS, TTS, s=10, marker='o', c='r', alpha=0.4, label='S')
# plt.legend('upper right')
# plt.show()
print('The Number of Realizations: ' + str(evid) + '\n', flush=True)
jj = json.dumps(traceNmae_dic)
if platform.system() == 'Windows':
f = open(save_dir + "\\" + "traceNmae_dic.json", "w")
else:
f = open(save_dir + "/" + "traceNmae_dic.json", "w")
f.write(jj)
f.close()
else:
if platform.system() == 'Windows':
Y2000_writer = open(save_dir + "\\" + "Y2000.phs", "w")
else:
Y2000_writer = open(save_dir + "/" + "Y2000.phs", "w")
cat = Catalog()
traceNmae_dic = dict()
st = datetime.strptime(start_time, '%Y-%m-%d %H:%M:%S.%f')
et = datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S.%f')
total_t = et - st
evid = 200000
evidd = 100000
tt = st
pbar = tqdm(total=int(np.ceil(total_t.total_seconds() /
moving_window)))
while tt < et:
detections = tbl[(tbl.event_start_time >= tt) & (
tbl.event_start_time < tt + timedelta(seconds=moving_window))]
pbar.update()
if len(detections) >= pair_n:
yr = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[0])
mo = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[1])
dy = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[0].split('-')[2])
hr = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[0])
mi = "{:>2}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[1])
sec = "{:>4}".format(
str(detections.iloc[0]['event_start_time']).split(' ')
[1].split(':')[2])
st_lat_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlat']), "Latitude")
st_lon_DMS = _decimalDegrees2DMS(
float(detections.iloc[0]['stlon']), "Longitude")
depth = 5.0
mag = 0.0
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi), float(sec),
float(st_lat_DMS[0]), str(st_lat_DMS[1]),
float(st_lat_DMS[2]), float(st_lon_DMS[0]),
str(st_lon_DMS[1]), float(
st_lon_DMS[2]), float(depth), float(mag)))
event = Event()
origin = Origin(time=UTCDateTime(
detections.iloc[0]['event_start_time']),
longitude=detections.iloc[0]['stlon'],
latitude=detections.iloc[0]['stlat'],
method="EqTransformer")
event.origins.append(origin)
station_buffer = []
row_buffer = []
sorted_detections = detections.sort_values('p_arrival_time')
tr_names = []
tr_names2 = []
picks = []
for _, row in sorted_detections.iterrows():
trace_name = row['traceID'] + '*' + row[
'station'] + '*' + str(row['event_start_time'])
p_unc = row['p_unc']
p_prob = row['p_prob']
s_unc = row['s_unc']
s_prob = row['s_prob']
if p_unc:
Pweihgt = _weighcalculator_prob(p_prob * (1 - p_unc))
else:
Pweihgt = _weighcalculator_prob(p_prob)
try:
Pweihgt = int(Pweihgt)
except Exception:
Pweihgt = 4
if s_unc:
Sweihgt = _weighcalculator_prob(s_prob * (1 - s_unc))
else:
Sweihgt = _weighcalculator_prob(s_prob)
try:
Sweihgt = int(Sweihgt)
except Exception:
Sweihgt = 4
station = "{:<5}".format(row['station'])
network = "{:<2}".format(row['network'])
try:
yrp = "{:>4}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[0])
mop = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[1])
dyp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[0].split('-')
[2])
hrp = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[0])
mip = "{:>2}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[1])
sec_p = "{:>4}".format(
str(row['p_arrival_time']).split(' ')[1].split(':')
[2])
p = Pick(time=UTCDateTime(row['p_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="P",
method_id="EqTransformer")
picks.append(p)
except Exception:
sec_p = None
try:
yrs = "{:>4}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[0])
mos = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[1])
dys = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[0].split('-')
[2])
hrs = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[0])
mis = "{:>2}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[1])
sec_s = "{:>4}".format(
str(row['s_arrival_time']).split(' ')[1].split(':')
[2])
p = Pick(time=UTCDateTime(row['s_arrival_time']),
waveform_id=WaveformStreamID(
network_code=network,
station_code=station.rstrip()),
phase_hint="S",
method_id="EqTransformer")
picks.append(p)
except Exception:
sec_s = None
if row['station'] not in station_buffer:
tr_names.append(trace_name)
station_buffer.append(row['station'])
if sec_s:
Y2000_writer.write(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
% (station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), float(0.0),
float(sec_s), Sweihgt))
if sec_p:
Y2000_writer.write(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp), int(mip),
float(sec_p), float(0.0)))
else:
tr_names2.append(trace_name)
if sec_s:
row_buffer.append(
"%5s%2s HHE %4d%2d%2d%2d%2d%5.2f %5.2fES %1d\n"
% (station, network, int(yrs), int(mos),
int(dys), int(hrs), int(mis), 0.0,
float(sec_s), Sweihgt))
if sec_p:
row_buffer.append(
"%5s%2s HHZ IP %1d%4d%2d%2d%2d%2d%5.2f %5.2f 0\n"
% (station, network, Pweihgt, int(yrp),
int(mop), int(dyp), int(hrp), int(mip),
float(sec_p), float(0.0)))
event.picks = picks
event.preferred_origin_id = event.origins[0].resource_id
cat.append(event)
evid += 1
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names
if len(row_buffer) >= 2 * pair_n:
Y2000_writer.write(
"%4d%2d%2d%2d%2d%4.2f%2.0f%1s%4.2f%3.0f%1s%4.2f%5.2f%3.2f\n"
% (int(yr), int(mo), int(dy), int(hr), int(mi),
float(sec), float(st_lat_DMS[0]), str(
st_lat_DMS[1]), float(st_lat_DMS[2]),
float(st_lon_DMS[0]), str(st_lon_DMS[1]),
float(st_lon_DMS[2]), float(depth), float(mag)))
for rr in row_buffer:
Y2000_writer.write(rr)
evid += 1
Y2000_writer.write("{:<62}".format(' ') + "%10d" % (evid) +
'\n')
traceNmae_dic[str(evid)] = tr_names2
elif len(row_buffer) < pair_n and len(row_buffer) != 0:
evidd += 1
traceNmae_dic[str(evidd)] = tr_names2
elif len(detections) < pair_n and len(detections) != 0:
tr_names = []
for _, row in detections.iterrows():
trace_name = row['traceID']
tr_names.append(trace_name)
evidd += 1
traceNmae_dic[str(evidd)] = tr_names
tt += timedelta(seconds=moving_window)
print('The Number of Associated Events: ' + str(evid - 200000) + '\n',
flush=True)
jj = json.dumps(traceNmae_dic)
if platform.system() == 'Windows':
f = open(save_dir + "\\" + "traceNmae_dic.json", "w")
else:
f = open(save_dir + "/" + "traceNmae_dic.json", "w")
f.write(jj)
f.close()
print(cat.__str__(print_all=True))
cat.write(save_dir + "/associations.xml", format="QUAKEML")
def _load_events(self):
self._load_events_helper()
cache = {}
notFound = defaultdict(int)
oEvents = []
missingStations = defaultdict(int)
for e in self.eventList:
if (e.preferred_origin and len(e.preferred_origin.arrival_list)):
cullList = []
for a in e.preferred_origin.arrival_list:
if (len(a.net)): continue
seedid = '%s.%s.%s.%s' % (a.net, a.sta, a.loc, a.cha)
newCode = None
if (seedid not in cache):
sc = a.sta
lonlat = self.isc_coords_dict[sc]
if (len(lonlat) == 0):
cullList.append(a)
continue
# end if
r = self.fdsn_inventory.getClosestStations(lonlat[0],
lonlat[1],
maxdist=1e3)
#if(a.sta=='KUM'): print a.net, a.sta, a.loc, a.cha, r
if (not r):
notFound[sc] += 1
else:
for cr in r[0]:
c = cr.split('.')[0]
newCode = c
# end for
# end if
if (newCode):
cache[seedid] = newCode
# end if
else:
newCode = cache[seedid]
# end if
if (newCode):
#print a.net, newCode
a.net = newCode
sc = self.fdsn_inventory.t[a.net][a.sta]
if (type(sc) == defaultdict):
cullList.append(a)
continue
# end if
da = gps2dist_azimuth(e.preferred_origin.lat,
e.preferred_origin.lon, sc[1],
sc[0])
dist = kilometers2degrees(da[0] / 1e3)
if (np.fabs(a.distance - dist) > 0.5):
cullList.append(a)
# end if
# end if
# end for
for c in cullList:
e.preferred_origin.arrival_list.remove(c)
# end if
# Create obspy event object
ci = OCreationInfo(author='GA',
creation_time=UTCDateTime(),
agency_id='GA-iteration-1')
oid = self.get_id()
origin = OOrigin(resource_id=OResourceIdentifier(id=oid),
time=UTCDateTime(e.preferred_origin.utctime),
longitude=e.preferred_origin.lon,
latitude=e.preferred_origin.lat,
depth=e.preferred_origin.depthkm * 1e3,
method_id=OResourceIdentifier(id='unknown'),
earth_model_id=OResourceIdentifier(id='iasp91'),
evaluation_mode='automatic',
creation_info=ci)
magnitude = OMagnitude(
resource_id=OResourceIdentifier(id=self.get_id()),
mag=e.preferred_magnitude.magnitude_value,
magnitude_type=e.preferred_magnitude.magnitude_type,
origin_id=OResourceIdentifier(id=oid),
creation_info=ci)
event = OEvent(resource_id=OResourceIdentifier(id=self.get_id()),
creation_info=ci,
event_type='earthquake')
event.origins = [origin]
event.magnitudes = [magnitude]
event.preferred_magnitude_id = magnitude.resource_id
event.preferred_origin_id = origin.resource_id
# Insert old picks
for a in e.preferred_origin.arrival_list:
if (type(self.fdsn_inventory.t[a.net][a.sta]) == defaultdict):
missingStations[a.net + '.' + a.sta] += 1
continue
# end if
oldPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(a.utctime),
waveform_id=OWaveformStreamID(network_code=a.net,
station_code=a.sta,
channel_code=a.cha),
methodID=OResourceIdentifier('unknown'),
phase_hint=a.phase,
evaluation_mode='automatic',
creation_info=ci)
oldArr = OArrival(resource_id=OResourceIdentifier(
id=oldPick.resource_id.id + "#"),
pick_id=oldPick.resource_id,
phase=oldPick.phase_hint,
distance=a.distance,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(oldPick)
event.preferred_origin().arrivals.append(oldArr)
# end for
# Insert our picks
opList = self.our_picks.picks[e.public_id]
if (len(opList)):
for op in opList:
if (type(self.fdsn_inventory.t[op[1]][op[2]]) ==
defaultdict):
missingStations[op[1] + '.' + op[2]] += 1
continue
# end if
newPick = OPick(
resource_id=OResourceIdentifier(id=self.get_id()),
time=UTCDateTime(op[0]),
waveform_id=OWaveformStreamID(network_code=op[1],
station_code=op[2],
channel_code=op[3]),
methodID=OResourceIdentifier('phasepapy/aicd'),
backazimuth=op[-1],
phase_hint=op[4],
evaluation_mode='automatic',
comments=op[6],
creation_info=ci)
newArr = OArrival(
resource_id=OResourceIdentifier(
id=newPick.resource_id.id + "#"),
pick_id=newPick.resource_id,
phase=newPick.phase_hint,
azimuth=op[-2],
distance=op[-3],
time_residual=op[5],
time_weight=1.,
earth_model_id=OResourceIdentifier(
'quakeml:ga.gov.au/earthmodel/iasp91'),
creation_info=ci)
event.picks.append(newPick)
event.preferred_origin().arrivals.append(newArr)
# end for
# end if
quality = OOriginQuality(
associated_phase_count=len(e.preferred_origin.arrival_list) +
len(self.our_picks.picks[e.public_id]),
used_phase_count=len(e.preferred_origin.arrival_list) +
len(self.our_picks.picks[e.public_id]))
event.preferred_origin().quality = quality
oEvents.append(event)
# end for // loop over e
#print notFound
print self.rank, missingStations
cat = OCatalog(events=oEvents)
ofn = self.output_path + '/%d.xml' % (self.rank)
cat.write(ofn, format='SC3ML')
def sdxtoquakeml(sdx_dir, out_xml,
time_uncertainties=[0.1, 0.2, 0.5, 0.8, 1.5],
catalog_description="", catalog_version="",
agency_id="", author="", vel_mod_id=""):
"""
Convert SDX to QuakeML format using ObsPy inventory structure.
SDX filename prefix is stored under event description.
Input parameters:
- sdx_dir: directory containing sdx files (required)
- out_xml: Filename of quakeML file (required)
- time_uncertainties: List containing time uncertainities in seconds
for mapping from weights 0-4, respectively (optional)
- catalog_description (optional)
- cat_agency_id (optional)
- author (optional)
- vel_mod_id (optional)
Output:
- xml catalog in QuakeML format.
"""
# Prepare catalog
cat = Catalog(description=catalog_description,
creation_info=CreationInfo(
author=author, agency_id=agency_id,
version=catalog_version))
# Read in sdx files in directory, recursively
files = glob.glob("{:}/**/*.sdx".format(sdx_dir), recursive=True)
if len(files) == 0:
print("No SDX files found in path. Exiting")
for sdx_file_path in files:
print("Working on ", sdx_file_path.split('/')[-1])
# Set-up event
evt_id = (sdx_file_path.split('/')[-1])[:-4]
event = Event(event_type="earthquake", creation_info=CreationInfo(
author=author, agency_id=agency_id),
event_descriptions=[EventDescription(text=evt_id)])
# Get station details, append to arrays
sdx_file = open(sdx_file_path, "r")
stations = []
for line in sdx_file:
if line.rstrip() == "station":
sdxstation = list(islice(sdx_file, 5))
stations.append([sdxstation[1].split()[0],
float(sdxstation[2].split()[0]),
float(sdxstation[3].split()[0]),
float(sdxstation[4].split()[0])])
sdx_file.close()
# Find origin details, append to origin object
sdx_file = open(sdx_file_path, "r")
found_origin = False
for line in sdx_file:
if line.rstrip() == "origin":
found_origin = True
sdxorigin = list(islice(sdx_file, 17))
orig_time = ("{:}T{:}".
format(sdxorigin[1][0:10].replace(".", "-"),
sdxorigin[1][11:23]))
evt_lat = float(sdxorigin[2].split()[0])
evt_lon = float(sdxorigin[3].split()[0])
evt_depth = float(sdxorigin[4].split()[0])
creation_time = UTCDateTime(
"{:}T{:}".format(sdxorigin[16].split()[6][0:10]
.replace(".", "-"),
sdxorigin[16].split()[6][11:23]))
num_arrivals = int(sdxorigin[12].split()[0])
num_arrivals_p = (int(sdxorigin[12].split()[0]) -
int(sdxorigin[12].split()[1]))
min_dist = float(sdxorigin[12].split()[9])
max_dist = float(sdxorigin[12].split()[10])
med_dist = float(sdxorigin[12].split()[11])
max_az_gap = float(sdxorigin[12].split()[6])
origin = Origin(time=UTCDateTime(orig_time), longitude=evt_lon,
latitude=evt_lat, depth=evt_depth*-1000,
earth_model_id=vel_mod_id,
origin_type="hypocenter",
evaluation_mode="manual",
evaluation_status="confirmed",
method_id=ResourceIdentifier(id="SDX_hypo71"),
creation_info=CreationInfo(
creation_time=creation_time, author=author,
agency_id=agency_id),
quality=OriginQuality(
associated_phase_count=num_arrivals,
used_phase_count=num_arrivals,
associated_station_count=num_arrivals_p,
used_station_count=num_arrivals_p,
azimuthal_gap=max_az_gap,
minimum_distance=min_dist,
maximum_distance=max_dist,
median_distance=med_dist))
event.origins.append(origin)
sdx_file.close()
# Skip event if no computed origin
if found_origin is False:
print("No origin found ... skipping event")
continue
# Get pick details, append to pick and arrival objects
sdx_file = open(sdx_file_path, "r")
found_pick = False
for line in sdx_file:
if line.rstrip() == "pick":
found_pick = True
sdxpick = list(islice(sdx_file, 15))
pick_time = UTCDateTime(
"{:}T{:}".format(sdxpick[1][0:10].replace(".", "-"),
sdxpick[1][11:23]))
network = sdxpick[2].split()[0]
station = sdxpick[2].split()[1]
location = sdxpick[2].split()[2]
if "NOT_SET" in location:
location = ""
channel = sdxpick[2].split()[3]
onset = sdxpick[8].split()[0]
if onset == "0":
pickonset = "emergent"
elif onset == "1":
pickonset = "impulsive"
elif onset == "2":
pickonset = "questionable"
phase = sdxpick[9].split()[0]
polarity = sdxpick[10].split()[0]
if polarity == "0":
pol = "positive"
elif polarity == "1":
pol = "negative"
elif polarity == "2":
pol = "undecidable"
weight = int(sdxpick[11].split()[0])
creation_time = UTCDateTime(
"{:}T{:}".format(sdxpick[14].split()[6][0:10]
.replace(".", "-"),
sdxpick[14].split()[6][11:23]))
pick = Pick(time=pick_time,
waveform_id=WaveformStreamID(
network_code=network, station_code=station,
location_code=location, channel_code=channel),
time_errors=time_uncertainties[weight],
evaluation_mode="manual",
evaluation_status="confirmed", onset=pickonset,
phase_hint=phase, polarity=pol,
method_id=ResourceIdentifier(id="SDX"),
creation_info=CreationInfo(
creation_time=creation_time))
event.picks.append(pick)
# Compute azimuth, distance, append to arrival object
for i in range(0, len(stations)):
if stations[i][0] == station:
azimuth = (gps2dist_azimuth(evt_lat, evt_lon,
stations[i][1],
stations[i][2])[1])
dist_deg = locations2degrees(evt_lat, evt_lon,
stations[i][1],
stations[i][2])
arrival = Arrival(phase=phase,
pick_id=pick.resource_id,
azimuth=azimuth, distance=dist_deg,
time_weight=1.00)
event.origins[0].arrivals.append(arrival)
# Skip event if no picks
if found_pick is False:
print("No picks found ... skipping event")
continue
# Set preferred origin and append event to catalogue
event.preferred_origin_id = event.origins[0].resource_id
cat.events.append(event)
sdx_file.close()
cat.write(out_xml, format="QUAKEML")
def _readheader(f):
"""
Internal header reader.
:type f: file
:param f: File open in read-mode.
:returns: :class:`~obspy.core.event.event.Event`
"""
f.seek(0)
# Base populate to allow for empty parts of file
new_event = Event()
topline = _get_headline(f=f)
if not topline:
raise NordicParsingError('No header found, or incorrect '
'formatting: corrupt s-file')
try:
sfile_seconds = int(topline[16:18])
if sfile_seconds == 60:
sfile_seconds = 0
add_seconds = 60
else:
add_seconds = 0
new_event.origins.append(Origin())
new_event.origins[0].time = UTCDateTime(int(topline[1:5]),
int(topline[6:8]),
int(topline[8:10]),
int(topline[11:13]),
int(topline[13:15]),
sfile_seconds,
int(topline[19:20]) *
100000)\
+ add_seconds
except Exception:
NordicParsingError("Couldn't read a date from sfile")
# new_event.loc_mod_ind=topline[20]
new_event.event_descriptions.append(EventDescription())
new_event.event_descriptions[0].text = topline[21:23]
# new_event.ev_id=topline[22]
try:
new_event.origins[0].latitude = float(topline[23:30])
new_event.origins[0].longitude = float(topline[31:38])
new_event.origins[0].depth = float(topline[39:43]) * 1000
except ValueError:
# The origin 'requires' a lat & long
new_event.origins[0].latitude = None
new_event.origins[0].longitude = None
new_event.origins[0].depth = None
# new_event.depth_ind = topline[44]
# new_event.loc_ind = topline[45]
new_event.creation_info = CreationInfo(agency_id=topline[45:48].strip())
ksta = Comment(text='Number of stations=' + topline[49:51].strip())
new_event.origins[0].comments.append(ksta)
if _float_conv(topline[51:55]) is not None:
new_event.origins[0].quality = OriginQuality(
standard_error=_float_conv(topline[51:55]))
# Read in magnitudes if they are there.
for index in [59, 67, 75]:
if not topline[index].isspace():
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[-1].mag = _float_conv(topline[index -
3:index])
new_event.magnitudes[-1].magnitude_type = \
_nortoevmag(topline[index])
new_event.magnitudes[-1].creation_info = \
CreationInfo(agency_id=topline[index + 1:index + 4].strip())
new_event.magnitudes[-1].origin_id = new_event.origins[0].\
resource_id
# Set the useful things like preferred magnitude and preferred origin
new_event.preferred_origin_id = new_event.origins[0].resource_id
try:
# Select moment first, then local, then
mag_filter = [
'MW', 'Mw', 'ML', 'Ml', 'MB', 'Mb', 'MS', 'Ms', 'MC', 'Mc'
]
_magnitudes = [(m.magnitude_type, m.resource_id)
for m in new_event.magnitudes]
preferred_magnitude = sorted(_magnitudes,
key=lambda x: mag_filter.index(x[0]))[0]
new_event.preferred_magnitude_id = preferred_magnitude[1]
except (ValueError, IndexError):
# If there is a magnitude not specified in filter
try:
new_event.preferred_magnitude_id = new_event.magnitudes[0].\
resource_id
except IndexError:
pass
return new_event
def _internal_read_single_scardec(buf):
"""
Reads a single SCARDEC file to a :class:`~obspy.core.event.Catalog`
object.
:param buf: File to read.
:type buf: open file or file-like object
"""
# The first line encodes the origin time and epicenter
line = buf.readline()
origin_time = line.strip().split()[:6]
values = list(map(int, origin_time[:-1])) + \
[float(origin_time[-1])]
try:
origin_time = UTCDateTime(*values)
except (TypeError, ValueError):
warnings.warn("Could not determine origin time from line: %s. Will "
"be set to zero." % line)
origin_time = UTCDateTime(0)
line = line.split()[6:]
latitude, longitude = map(float, line[:2])
# The second line encodes depth and the two focal mechanisms
line = buf.readline()
line = line.split()
# First three values are depth, scalar moment (in Nm) and moment magnitude
depth, scalar_moment, moment_mag = map(float, line[0:3])
# depth is in km in SCARDEC files
depth *= 1e3
# Next six values are strike, dip, rake for both planes
strike1, dip1, rake1 = map(float, line[3:6])
strike2, dip2, rake2 = map(float, line[6:9])
# The rest of the file is the moment rate function
# In each line: time (sec), moment rate (Nm/sec)
stf_time = []
stf_mr = []
for line in buf:
stf_time.append(float(line.split()[0]))
stf_mr.append(float(line.split()[1]))
# Normalize the source time function
stf_mr = np.array(stf_mr)
stf_mr /= scalar_moment
# Calculate the time step
dt = np.mean(np.diff(stf_time))
# Calculate the stf offset (time of first sample wrt to origin time)
offset = stf_time[0]
# event name is set to generic value for now
event_name = 'SCARDEC_event'
cmt_origin = Origin(resource_id=_get_resource_id(event_name,
"origin",
tag="cmt"),
time=origin_time,
longitude=longitude,
latitude=latitude,
depth=depth,
origin_type="centroid",
region=_fe.get_region(longitude=longitude,
latitude=latitude))
cmt_mag = Magnitude(resource_id=_get_resource_id(event_name,
"magnitude",
tag="mw"),
mag=moment_mag,
magnitude_type="mw",
origin_id=cmt_origin.resource_id)
nod1 = NodalPlane(strike=strike1, dip=dip1, rake=rake1)
nod2 = NodalPlane(strike=strike2, dip=dip2, rake=rake2)
nod = NodalPlanes(nodal_plane_1=nod1, nodal_plane_2=nod2)
foc_mec = FocalMechanism(resource_id=_get_resource_id(
event_name, "focal_mechanism"),
nodal_planes=nod)
dip1 *= np.pi / 180.
rake1 *= np.pi / 180.
strike1 *= np.pi / 180.
mxx = -scalar_moment * (
(np.sin(dip1) * np.cos(rake1) * np.sin(2 * strike1)) +
(np.sin(2 * dip1) * np.sin(rake1) * np.sin(2 * strike1)))
mxy = scalar_moment * (
(np.sin(dip1) * np.cos(rake1) * np.cos(2 * strike1)) +
(np.sin(2 * dip1) * np.sin(rake1) * np.sin(2 * strike1) * 0.5))
myy = scalar_moment * (
(np.sin(dip1) * np.cos(rake1) * np.sin(2 * strike1)) -
(np.sin(2 * dip1) * np.sin(rake1) * np.cos(2 * strike1)))
mxz = -scalar_moment * (
(np.cos(dip1) * np.cos(rake1) * np.cos(strike1)) +
(np.cos(2 * dip1) * np.sin(rake1) * np.sin(strike1)))
myz = -scalar_moment * (
(np.cos(dip1) * np.cos(rake1) * np.sin(strike1)) -
(np.cos(2 * dip1) * np.sin(rake1) * np.cos(strike1)))
mzz = scalar_moment * (np.sin(2 * dip1) * np.sin(rake1))
tensor = Tensor(m_rr=mxx, m_tt=myy, m_pp=mzz, m_rt=mxy, m_rp=mxz, m_tp=myz)
cm = [
Comment(text="Basis system: North,East,Down \
(Jost and Herrmann 1989)")
]
cm[0].resource_id = _get_resource_id(event_name, 'comment', 'mt')
cm.append(
Comment(text="MT derived from focal mechanism, therefore \
constrained to pure double couple.",
force_resource_id=False))
# Write moment rate function
extra = {
'moment_rate': {
'value': stf_mr,
'namespace': r"http://test.org/xmlns/0.1"
},
'dt': {
'value': dt,
'namespace': r"http://test.org/xmlns/0.1"
},
'offset': {
'value': offset,
'namespace': r"http://test.org/xmlns/0.1"
}
}
# Source time function
stf = SourceTimeFunction(type="unknown")
stf.extra = extra
mt = MomentTensor(resource_id=_get_resource_id(event_name,
"moment_tensor"),
derived_origin_id=cmt_origin.resource_id,
moment_magnitude_id=cmt_mag.resource_id,
scalar_moment=scalar_moment,
tensor=tensor,
source_time_function=stf,
comments=cm)
# Assemble everything.
foc_mec.moment_tensor = mt
ev = Event(resource_id=_get_resource_id(event_name, "event"),
event_type="earthquake")
ev.event_descriptions.append(
EventDescription(text=event_name, type="earthquake name"))
ev.comments.append(
Comment(text="Hypocenter catalog: SCARDEC", force_resource_id=False))
ev.origins.append(cmt_origin)
ev.magnitudes.append(cmt_mag)
ev.focal_mechanisms.append(foc_mec)
# Set the preferred items.
ev.preferred_origin_id = cmt_origin.resource_id.id
ev.preferred_magnitude_id = cmt_mag.resource_id.id
ev.preferred_focal_mechanism_id = foc_mec.resource_id.id
ev.scope_resource_ids()
return ev
# Make picks for detections from template picks
det_picks = []
for p in template_event.picks:
delay_template = p.time - min_template_starttime
det_pick_time = detect_time + delay_template
pick = Pick(time=det_pick_time,
phase_hint=p.phase_hint,
waveform_id=p.waveform_id)
det_picks.append(pick)
# figure out origin time for detection
pick1_temp = template_event.picks[0]
origin_det = template_event.origins[0].copy()
pick1_det = [
p for p in det_picks if p.waveform_id == pick1_temp.waveform_id
][0]
origin_det.time = pick1_det.time - (pick1_temp.time -
template_event.origins[0].time)
# Create and save event for detection
event = Event(picks=det_picks, origins=[origin_det])
event.preferred_origin_id = event.origins[0].resource_id
catalog.append(event)
catalog_dir = os.path.join(os.getcwd(), "families_events")
catalog_fname = "catalog_" + family_name.split(".")[0] + ".xml"
catalog_file = os.path.join(catalog_dir, catalog_fname)
Logger.info("Now writing catalogue to file %s" % catalog_file)
catalog.write(catalog_file, format="QUAKEML")
def __read_single_fnetmt_entry(line, **kwargs):
"""
Reads a single F-net moment tensor solution to a
:class:`~obspy.core.event.Event` object.
:param line: String containing moment tensor information.
:type line: str.
"""
a = line.split()
try:
ot = UTCDateTime().strptime(a[0], '%Y/%m/%d,%H:%M:%S.%f')
except ValueError:
ot = UTCDateTime().strptime(a[0], '%Y/%m/%d,%H:%M:%S')
lat, lon, depjma, magjma = map(float, a[1:5])
depjma *= 1000
region = a[5]
strike = tuple(map(int, a[6].split(';')))
dip = tuple(map(int, a[7].split(';')))
rake = tuple(map(int, a[8].split(';')))
mo = float(a[9])
depmt = float(a[10]) * 1000
magmt = float(a[11])
var_red = float(a[12])
mxx, mxy, mxz, myy, myz, mzz, unit = map(float, a[13:20])
event_name = util.gen_sc3_id(ot)
e = Event(event_type="earthquake")
e.resource_id = _get_resource_id(event_name, 'event')
# Standard JMA solution
o_jma = Origin(time=ot,
latitude=lat,
longitude=lon,
depth=depjma,
depth_type="from location",
region=region)
o_jma.resource_id = _get_resource_id(event_name, 'origin', 'JMA')
m_jma = Magnitude(mag=magjma,
magnitude_type='ML',
origin_id=o_jma.resource_id)
m_jma.resource_id = _get_resource_id(event_name, 'magnitude', 'JMA')
# MT solution
o_mt = Origin(time=ot,
latitude=lat,
longitude=lon,
depth=depmt,
region=region,
depth_type="from moment tensor inversion")
o_mt.resource_id = _get_resource_id(event_name, 'origin', 'MT')
m_mt = Magnitude(mag=magmt,
magnitude_type='Mw',
origin_id=o_mt.resource_id)
m_mt.resource_id = _get_resource_id(event_name, 'magnitude', 'MT')
foc_mec = FocalMechanism(triggering_origin_id=o_jma.resource_id)
foc_mec.resource_id = _get_resource_id(event_name, "focal_mechanism")
nod1 = NodalPlane(strike=strike[0], dip=dip[0], rake=rake[0])
nod2 = NodalPlane(strike=strike[1], dip=dip[1], rake=rake[1])
nod = NodalPlanes(nodal_plane_1=nod1, nodal_plane_2=nod2)
foc_mec.nodal_planes = nod
tensor = Tensor(m_rr=mxx, m_tt=myy, m_pp=mzz, m_rt=mxy, m_rp=mxz, m_tp=myz)
cm = Comment(text="Basis system: North,East,Down (Jost and \
Herrmann 1989")
cm.resource_id = _get_resource_id(event_name, 'comment', 'mt')
mt = MomentTensor(derived_origin_id=o_mt.resource_id,
moment_magnitude_id=m_mt.resource_id,
scalar_moment=mo,
comments=[cm],
tensor=tensor,
variance_reduction=var_red)
mt.resource_id = _get_resource_id(event_name, 'moment_tensor')
foc_mec.moment_tensor = mt
e.origins = [o_jma, o_mt]
e.magnitudes = [m_jma, m_mt]
e.focal_mechanisms = [foc_mec]
e.preferred_magnitude_id = m_mt.resource_id.id
e.preferred_origin_id = o_mt.resource_id.id
e.preferred_focal_mechanism_id = foc_mec.resource_id.id
return e
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 __read_single_cmtsolution(buf):
"""
Reads a single CMTSOLUTION file to a :class:`~obspy.core.event.Catalog`
object.
:param buf: File to read.
:type buf: Open file or open file like object.
"""
# The first line encodes the preliminary epicenter.
line = buf.readline()
hypocenter_catalog = line[:4].strip().decode()
origin_time = line[4:].strip().split()[:6]
values = list(map(int, origin_time[:-1])) + \
[float(origin_time[-1])]
try:
origin_time = UTCDateTime(*values)
except (TypeError, ValueError):
warnings.warn("Could not determine origin time from line: %s. Will "
"be set to zero." % line)
origin_time = UTCDateTime(0)
line = line.split()[7:]
latitude, longitude, depth, body_wave_mag, surface_wave_mag = \
map(float, line[:5])
# The rest encodes the centroid solution.
event_name = buf.readline().strip().split()[-1].decode()
preliminary_origin = Origin(
resource_id=_get_resource_id(event_name, "origin", tag="prelim"),
time=origin_time,
longitude=longitude,
latitude=latitude,
# Depth is in meters.
depth=depth * 1000.0,
origin_type="hypocenter",
region=_fe.get_region(longitude=longitude, latitude=latitude),
evaluation_status="preliminary"
)
preliminary_bw_magnitude = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="prelim_bw"),
mag=body_wave_mag, magnitude_type="Mb",
evaluation_status="preliminary",
origin_id=preliminary_origin.resource_id)
preliminary_sw_magnitude = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="prelim_sw"),
mag=surface_wave_mag, magnitude_type="MS",
evaluation_status="preliminary",
origin_id=preliminary_origin.resource_id)
values = ["time_shift", "half_duration", "latitude", "longitude",
"depth", "m_rr", "m_tt", "m_pp", "m_rt", "m_rp", "m_tp"]
cmt_values = {_i: float(buf.readline().strip().split()[-1])
for _i in values}
# Moment magnitude calculation in dyne * cm.
m_0 = 1.0 / math.sqrt(2.0) * math.sqrt(
cmt_values["m_rr"] ** 2 +
cmt_values["m_tt"] ** 2 +
cmt_values["m_pp"] ** 2 +
2.0 * cmt_values["m_rt"] ** 2 +
2.0 * cmt_values["m_rp"] ** 2 +
2.0 * cmt_values["m_tp"] ** 2)
m_w = 2.0 / 3.0 * (math.log10(m_0) - 16.1)
# Convert to meters.
cmt_values["depth"] *= 1000.0
# Convert to Newton meter.
values = ["m_rr", "m_tt", "m_pp", "m_rt", "m_rp", "m_tp"]
for value in values:
cmt_values[value] /= 1E7
cmt_origin = Origin(
resource_id=_get_resource_id(event_name, "origin", tag="cmt"),
time=origin_time + cmt_values["time_shift"],
longitude=cmt_values["longitude"],
latitude=cmt_values["latitude"],
depth=cmt_values["depth"],
origin_type="centroid",
# Could rarely be different than the epicentral region.
region=_fe.get_region(longitude=cmt_values["longitude"],
latitude=cmt_values["latitude"])
# No evaluation status as it could be any of several and the file
# format does not provide that information.
)
cmt_mag = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="mw"),
# Round to 2 digits.
mag=round(m_w, 2),
magnitude_type="mw",
origin_id=cmt_origin.resource_id
)
foc_mec = FocalMechanism(
resource_id=_get_resource_id(event_name, "focal_mechanism"),
# The preliminary origin most likely triggered the focal mechanism
# determination.
triggering_origin_id=preliminary_origin.resource_id
)
tensor = Tensor(
m_rr=cmt_values["m_rr"],
m_pp=cmt_values["m_pp"],
m_tt=cmt_values["m_tt"],
m_rt=cmt_values["m_rt"],
m_rp=cmt_values["m_rp"],
m_tp=cmt_values["m_tp"]
)
# Source time function is a triangle, according to the SPECFEM manual.
stf = SourceTimeFunction(
type="triangle",
# The duration is twice the half duration.
duration=2.0 * cmt_values["half_duration"]
)
mt = MomentTensor(
resource_id=_get_resource_id(event_name, "moment_tensor"),
derived_origin_id=cmt_origin.resource_id,
moment_magnitude_id=cmt_mag.resource_id,
# Convert to Nm.
scalar_moment=m_0 / 1E7,
tensor=tensor,
source_time_function=stf
)
# Assemble everything.
foc_mec.moment_tensor = mt
ev = Event(resource_id=_get_resource_id(event_name, "event"),
event_type="earthquake")
ev.event_descriptions.append(EventDescription(text=event_name,
type="earthquake name"))
ev.comments.append(Comment(
text="Hypocenter catalog: %s" % hypocenter_catalog,
force_resource_id=False))
ev.origins.append(cmt_origin)
ev.origins.append(preliminary_origin)
ev.magnitudes.append(cmt_mag)
ev.magnitudes.append(preliminary_bw_magnitude)
ev.magnitudes.append(preliminary_sw_magnitude)
ev.focal_mechanisms.append(foc_mec)
# Set the preferred items.
ev.preferred_origin_id = cmt_origin.resource_id.id
ev.preferred_magnitude_id = cmt_mag.resource_id.id
ev.preferred_focal_mechanism_id = foc_mec.resource_id.id
return ev
def readheader(sfile):
"""
Read header information from a seisan nordic format S-file.
Returns an obspy.core.event.Catalog type: note this changed for version \
0.1.0 from the inbuilt class types.
:type sfile: str
:param sfile: Path to the s-file
:returns: :class: obspy.core.event.Event
>>> event = readheader('eqcorrscan/tests/test_data/REA/TEST_/' +
... '01-0411-15L.S201309')
>>> print(event.origins[0].time)
2013-09-01T04:11:15.700000Z
"""
import warnings
from obspy.core.event import Event, Origin, Magnitude, Comment
from obspy.core.event import EventDescription, CreationInfo
f = open(sfile, 'r')
# Base populate to allow for empty parts of file
new_event = Event()
topline = f.readline()
if not len(topline.rstrip()) == 80:
raise IOError('s-file has a corrupt header, not 80 char long')
f.seek(0)
for line in f:
if line[79] in [' ', '1']:
topline = line
break
if line[79] == '7':
raise IOError('No header found, corrupt s-file?')
try:
sfile_seconds = int(topline[16:18])
if sfile_seconds == 60:
sfile_seconds = 0
add_seconds = 60
else:
add_seconds = 0
new_event.origins.append(Origin())
new_event.origins[0].time = UTCDateTime(int(topline[1:5]),
int(topline[6:8]),
int(topline[8:10]),
int(topline[11:13]),
int(topline[13:15]),
sfile_seconds,
int(topline[19:20]) *
100000)\
+ add_seconds
except:
warnings.warn("Couldn't read a date from sfile: " + sfile)
new_event.origins.append(Origin(time=UTCDateTime(0)))
# new_event.loc_mod_ind=topline[20]
new_event.event_descriptions.append(EventDescription())
new_event.event_descriptions[0].text = topline[21:23]
# new_event.ev_id=topline[22]
if not _float_conv(topline[23:30]) == 999:
new_event.origins[0].latitude = _float_conv(topline[23:30])
new_event.origins[0].longitude = _float_conv(topline[31:38])
new_event.origins[0].depth = _float_conv(topline[39:43]) * 1000
else:
# The origin 'requires' a lat & long
new_event.origins[0].latitude = float('NaN')
new_event.origins[0].longitude = float('NaN')
new_event.origins[0].depth = float('NaN')
# new_event.depth_ind = topline[44]
# new_event.loc_ind = topline[45]
new_event.creation_info = CreationInfo(agency_id=topline[45:48].
strip())
ksta = Comment(text='Number of stations=' +
topline[49:51].strip())
new_event.origins[0].comments.append(ksta)
# new_event.origins[0].nsta??? = _int_conv(topline[49:51])
if not _float_conv(topline[51:55]) == 999:
new_event.origins[0].time_errors['Time_Residual_RMS'] = \
_float_conv(topline[51:55])
# Read in magnitudes if they are there.
if len(topline[59].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[0].mag = _float_conv(topline[56:59])
new_event.magnitudes[0].magnitude_type = topline[59]
new_event.magnitudes[0].creation_info = \
CreationInfo(agency_id=topline[60:63].strip())
new_event.magnitudes[0].origin_id = new_event.origins[0].\
resource_id
if len(topline[67].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[1].mag = _float_conv(topline[64:67])
new_event.magnitudes[1].magnitude_type = topline[67]
new_event.magnitudes[1].creation_info = \
CreationInfo(agency_id=topline[68:71].strip())
new_event.magnitudes[1].origin_id = new_event.origins[0].\
resource_id
if len(topline[75].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[2].mag = _float_conv(topline[72:75])
new_event.magnitudes[2].magnitude_type = topline[75]
new_event.magnitudes[2].creation_info = \
CreationInfo(agency_id=topline[76:79].strip())
new_event.magnitudes[2].origin_id = new_event.origins[0].\
resource_id
f.close()
# convert the nordic notation of magnitude to more general notation
for _magnitude in new_event.magnitudes:
_magnitude.magnitude_type = _nortoevmag(_magnitude.magnitude_type)
# Set the useful things like preferred magnitude and preferred origin
new_event.preferred_origin_id = str(new_event.origins[0].resource_id)
if len(new_event.magnitudes) > 1:
try:
# Select moment first, then local, then
mag_filter = ['MW', 'Mw', 'ML', 'Ml', 'MB', 'Mb',
'MS', 'Ms', 'Mc', 'MC']
_magnitudes = [(m.magnitude_type, m.resource_id)
for m in new_event.magnitudes]
preferred_magnitude = sorted(_magnitudes,
key=lambda x: mag_filter.index(x[0]))
new_event.preferred_magnitude_id = str(preferred_magnitude[0][1])
except ValueError:
# If there is a magnitude not specified in filter
new_event.preferred_magnitude_id =\
str(new_event.magnitudes[0].resource_id)
elif len(new_event.magnitudes) == 1:
new_event.preferred_magnitude_id =\
str(new_event.magnitudes[0].resource_id)
return new_event
def _internal_read_single_cmtsolution(buf):
"""
Reads a single CMTSOLUTION file to a :class:`~obspy.core.event.Catalog`
object.
:param buf: File to read.
:type buf: open file or file-like object
"""
# The first line encodes the preliminary epicenter.
line = buf.readline()
hypocenter_catalog = line[:5].strip().decode()
origin_time = line[5:].strip().split()[:6]
values = list(map(int, origin_time[:-1])) + \
[float(origin_time[-1])]
try:
origin_time = UTCDateTime(*values)
except (TypeError, ValueError):
warnings.warn("Could not determine origin time from line: %s. Will "
"be set to zero." % line)
origin_time = UTCDateTime(0)
line = line[28:].split()
latitude, longitude, depth, body_wave_mag, surface_wave_mag = \
map(float, line[:5])
# The rest encodes the centroid solution.
event_name = buf.readline().strip().split()[-1].decode()
preliminary_origin = Origin(
resource_id=_get_resource_id(event_name, "origin", tag="prelim"),
time=origin_time,
longitude=longitude,
latitude=latitude,
# Depth is in meters.
depth=depth * 1000.0,
origin_type="hypocenter",
region=_fe.get_region(longitude=longitude, latitude=latitude),
evaluation_status="preliminary")
preliminary_bw_magnitude = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="prelim_bw"),
mag=body_wave_mag,
magnitude_type="Mb",
evaluation_status="preliminary",
origin_id=preliminary_origin.resource_id)
preliminary_sw_magnitude = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="prelim_sw"),
mag=surface_wave_mag,
magnitude_type="MS",
evaluation_status="preliminary",
origin_id=preliminary_origin.resource_id)
values = [
"time_shift", "half_duration", "latitude", "longitude", "depth",
"m_rr", "m_tt", "m_pp", "m_rt", "m_rp", "m_tp"
]
cmt_values = {
_i: float(buf.readline().strip().split()[-1])
for _i in values
}
# Moment magnitude calculation in dyne * cm.
m_0 = 1.0 / math.sqrt(2.0) * math.sqrt(
cmt_values["m_rr"]**2 + cmt_values["m_tt"]**2 + cmt_values["m_pp"]**2 +
2.0 * cmt_values["m_rt"]**2 + 2.0 * cmt_values["m_rp"]**2 +
2.0 * cmt_values["m_tp"]**2)
m_w = 2.0 / 3.0 * (math.log10(m_0) - 16.1)
# Convert to meters.
cmt_values["depth"] *= 1000.0
# Convert to Newton meter.
values = ["m_rr", "m_tt", "m_pp", "m_rt", "m_rp", "m_tp"]
for value in values:
cmt_values[value] /= 1E7
cmt_origin = Origin(
resource_id=_get_resource_id(event_name, "origin", tag="cmt"),
time=origin_time + cmt_values["time_shift"],
longitude=cmt_values["longitude"],
latitude=cmt_values["latitude"],
depth=cmt_values["depth"],
origin_type="centroid",
# Could rarely be different than the epicentral region.
region=_fe.get_region(longitude=cmt_values["longitude"],
latitude=cmt_values["latitude"])
# No evaluation status as it could be any of several and the file
# format does not provide that information.
)
cmt_mag = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="mw"),
# Round to 2 digits.
mag=round(m_w, 2),
magnitude_type="mw",
origin_id=cmt_origin.resource_id)
foc_mec = FocalMechanism(
resource_id=_get_resource_id(event_name, "focal_mechanism"),
# The preliminary origin most likely triggered the focal mechanism
# determination.
triggering_origin_id=preliminary_origin.resource_id)
tensor = Tensor(m_rr=cmt_values["m_rr"],
m_pp=cmt_values["m_pp"],
m_tt=cmt_values["m_tt"],
m_rt=cmt_values["m_rt"],
m_rp=cmt_values["m_rp"],
m_tp=cmt_values["m_tp"])
# Source time function is a triangle, according to the SPECFEM manual.
stf = SourceTimeFunction(
type="triangle",
# The duration is twice the half duration.
duration=2.0 * cmt_values["half_duration"])
mt = MomentTensor(
resource_id=_get_resource_id(event_name, "moment_tensor"),
derived_origin_id=cmt_origin.resource_id,
moment_magnitude_id=cmt_mag.resource_id,
# Convert to Nm.
scalar_moment=m_0 / 1E7,
tensor=tensor,
source_time_function=stf)
# Assemble everything.
foc_mec.moment_tensor = mt
ev = Event(resource_id=_get_resource_id(event_name, "event"),
event_type="earthquake")
ev.event_descriptions.append(
EventDescription(text=event_name, type="earthquake name"))
ev.comments.append(
Comment(text="Hypocenter catalog: %s" % hypocenter_catalog,
force_resource_id=False))
ev.origins.append(cmt_origin)
ev.origins.append(preliminary_origin)
ev.magnitudes.append(cmt_mag)
ev.magnitudes.append(preliminary_bw_magnitude)
ev.magnitudes.append(preliminary_sw_magnitude)
ev.focal_mechanisms.append(foc_mec)
# Set the preferred items.
ev.preferred_origin_id = cmt_origin.resource_id.id
ev.preferred_magnitude_id = cmt_mag.resource_id.id
ev.preferred_focal_mechanism_id = foc_mec.resource_id.id
ev.scope_resource_ids()
return ev
def _readheader(f):
"""
Internal header reader.
:type f: file
:param f: File open in read-mode.
:returns: :class:`~obspy.core.event.event.Event`
"""
f.seek(0)
# Base populate to allow for empty parts of file
new_event = Event()
topline = _get_headline(f=f)
if not topline:
raise NordicParsingError('No header found, or incorrect '
'formatting: corrupt s-file')
try:
sfile_seconds = int(topline[16:18])
if sfile_seconds == 60:
sfile_seconds = 0
add_seconds = 60
else:
add_seconds = 0
new_event.origins.append(Origin())
new_event.origins[0].time = UTCDateTime(int(topline[1:5]),
int(topline[6:8]),
int(topline[8:10]),
int(topline[11:13]),
int(topline[13:15]),
sfile_seconds,
int(topline[19:20]) *
100000)\
+ add_seconds
except:
NordicParsingError("Couldn't read a date from sfile")
# new_event.loc_mod_ind=topline[20]
new_event.event_descriptions.append(EventDescription())
new_event.event_descriptions[0].text = topline[21:23]
# new_event.ev_id=topline[22]
try:
new_event.origins[0].latitude = float(topline[23:30])
new_event.origins[0].longitude = float(topline[31:38])
new_event.origins[0].depth = float(topline[39:43]) * 1000
except ValueError:
# The origin 'requires' a lat & long
new_event.origins[0].latitude = None
new_event.origins[0].longitude = None
new_event.origins[0].depth = None
# new_event.depth_ind = topline[44]
# new_event.loc_ind = topline[45]
new_event.creation_info = CreationInfo(agency_id=topline[45:48].strip())
ksta = Comment(text='Number of stations=' + topline[49:51].strip())
new_event.origins[0].comments.append(ksta)
if _float_conv(topline[51:55]) is not None:
new_event.origins[0].time_errors['Time_Residual_RMS'] = \
_float_conv(topline[51:55])
# Read in magnitudes if they are there.
for index in [59, 67, 75]:
if not topline[index].isspace():
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[-1].mag = _float_conv(
topline[index - 3:index])
new_event.magnitudes[-1].magnitude_type = \
_nortoevmag(topline[index])
new_event.magnitudes[-1].creation_info = \
CreationInfo(agency_id=topline[index + 1:index + 4].strip())
new_event.magnitudes[-1].origin_id = new_event.origins[0].\
resource_id
# Set the useful things like preferred magnitude and preferred origin
new_event.preferred_origin_id = new_event.origins[0].resource_id
try:
# Select moment first, then local, then
mag_filter = ['MW', 'Mw', 'ML', 'Ml', 'MB', 'Mb',
'MS', 'Ms', 'MC', 'Mc']
_magnitudes = [(m.magnitude_type, m.resource_id)
for m in new_event.magnitudes]
preferred_magnitude = sorted(_magnitudes,
key=lambda x: mag_filter.index(x[0]))[0]
new_event.preferred_magnitude_id = preferred_magnitude[1]
except (ValueError, IndexError):
# If there is a magnitude not specified in filter
try:
new_event.preferred_magnitude_id = new_event.magnitudes[0].\
resource_id
except IndexError:
pass
return new_event
def sdxtoquakeml(sdx_dir,
out_xml,
time_uncertainties=[0.1, 0.2, 0.5, 0.8, 1.5],
catalog_description="",
catalog_version="",
agency_id="",
author="",
vel_mod_id=""):
"""
Convert SDX to QuakeML format using ObsPy inventory structure.
SDX filename prefix is stored under event description.
Input parameters:
- sdx_dir: directory containing sdx files (required)
- out_xml: Filename of quakeML file (required)
- time_uncertainties: List containing time uncertainities in seconds
for mapping from weights 0-4, respectively (optional)
- catalog_description (optional)
- cat_agency_id (optional)
- author (optional)
- vel_mod_id (optional)
Output:
- xml catalog in QuakeML format.
"""
# Prepare catalog
cat = Catalog(description=catalog_description,
creation_info=CreationInfo(author=author,
agency_id=agency_id,
version=catalog_version))
# Read in sdx files in directory, recursively
files = glob.glob("{:}/**/*.sdx".format(sdx_dir), recursive=True)
if len(files) == 0:
print("No SDX files found in path. Exiting")
for sdx_file_path in files:
print("Working on ", sdx_file_path.split('/')[-1])
# Set-up event
evt_id = (sdx_file_path.split('/')[-1])[:-4]
event = Event(event_type="earthquake",
creation_info=CreationInfo(author=author,
agency_id=agency_id),
event_descriptions=[EventDescription(text=evt_id)])
# Get station details, append to arrays
sdx_file = open(sdx_file_path, "r")
stations = []
for line in sdx_file:
if line.rstrip() == "station":
sdxstation = list(islice(sdx_file, 5))
stations.append([
sdxstation[1].split()[0],
float(sdxstation[2].split()[0]),
float(sdxstation[3].split()[0]),
float(sdxstation[4].split()[0])
])
sdx_file.close()
# Find origin details, append to origin object
sdx_file = open(sdx_file_path, "r")
found_origin = False
for line in sdx_file:
if line.rstrip() == "origin":
found_origin = True
sdxorigin = list(islice(sdx_file, 17))
orig_time = ("{:}T{:}".format(
sdxorigin[1][0:10].replace(".", "-"), sdxorigin[1][11:23]))
evt_lat = float(sdxorigin[2].split()[0])
evt_lon = float(sdxorigin[3].split()[0])
evt_depth = float(sdxorigin[4].split()[0])
creation_time = UTCDateTime("{:}T{:}".format(
sdxorigin[16].split()[6][0:10].replace(".", "-"),
sdxorigin[16].split()[6][11:23]))
num_arrivals = int(sdxorigin[12].split()[0])
num_arrivals_p = (int(sdxorigin[12].split()[0]) -
int(sdxorigin[12].split()[1]))
min_dist = float(sdxorigin[12].split()[9])
max_dist = float(sdxorigin[12].split()[10])
med_dist = float(sdxorigin[12].split()[11])
max_az_gap = float(sdxorigin[12].split()[6])
origin = Origin(time=UTCDateTime(orig_time),
longitude=evt_lon,
latitude=evt_lat,
depth=evt_depth * -1000,
earth_model_id=vel_mod_id,
origin_type="hypocenter",
evaluation_mode="manual",
evaluation_status="confirmed",
method_id=ResourceIdentifier(id="SDX_hypo71"),
creation_info=CreationInfo(
creation_time=creation_time,
author=author,
agency_id=agency_id),
quality=OriginQuality(
associated_phase_count=num_arrivals,
used_phase_count=num_arrivals,
associated_station_count=num_arrivals_p,
used_station_count=num_arrivals_p,
azimuthal_gap=max_az_gap,
minimum_distance=min_dist,
maximum_distance=max_dist,
median_distance=med_dist))
event.origins.append(origin)
sdx_file.close()
# Skip event if no computed origin
if found_origin is False:
print("No origin found ... skipping event")
continue
# Get pick details, append to pick and arrival objects
sdx_file = open(sdx_file_path, "r")
found_pick = False
for line in sdx_file:
if line.rstrip() == "pick":
found_pick = True
sdxpick = list(islice(sdx_file, 15))
pick_time = UTCDateTime("{:}T{:}".format(
sdxpick[1][0:10].replace(".", "-"), sdxpick[1][11:23]))
network = sdxpick[2].split()[0]
station = sdxpick[2].split()[1]
location = sdxpick[2].split()[2]
if "NOT_SET" in location:
location = ""
channel = sdxpick[2].split()[3]
onset = sdxpick[8].split()[0]
if onset == "0":
pickonset = "emergent"
elif onset == "1":
pickonset = "impulsive"
elif onset == "2":
pickonset = "questionable"
phase = sdxpick[9].split()[0]
polarity = sdxpick[10].split()[0]
if polarity == "0":
pol = "positive"
elif polarity == "1":
pol = "negative"
elif polarity == "2":
pol = "undecidable"
weight = int(sdxpick[11].split()[0])
creation_time = UTCDateTime("{:}T{:}".format(
sdxpick[14].split()[6][0:10].replace(".", "-"),
sdxpick[14].split()[6][11:23]))
pick = Pick(
time=pick_time,
waveform_id=WaveformStreamID(network_code=network,
station_code=station,
location_code=location,
channel_code=channel),
time_errors=time_uncertainties[weight],
evaluation_mode="manual",
evaluation_status="confirmed",
onset=pickonset,
phase_hint=phase,
polarity=pol,
method_id=ResourceIdentifier(id="SDX"),
creation_info=CreationInfo(creation_time=creation_time))
event.picks.append(pick)
# Compute azimuth, distance, append to arrival object
for i in range(0, len(stations)):
if stations[i][0] == station:
azimuth = (gps2dist_azimuth(evt_lat, evt_lon,
stations[i][1],
stations[i][2])[1])
dist_deg = locations2degrees(evt_lat, evt_lon,
stations[i][1],
stations[i][2])
arrival = Arrival(phase=phase,
pick_id=pick.resource_id,
azimuth=azimuth,
distance=dist_deg,
time_weight=1.00)
event.origins[0].arrivals.append(arrival)
# Skip event if no picks
if found_pick is False:
print("No picks found ... skipping event")
continue
# Set preferred origin and append event to catalogue
event.preferred_origin_id = event.origins[0].resource_id
cat.events.append(event)
sdx_file.close()
cat.write(out_xml, format="QUAKEML")
def _read_single_hypocenter(lines, coordinate_converter, original_picks):
"""
Given a list of lines (starting with a 'NLLOC' line and ending with a
'END_NLLOC' line), parse them into an Event.
"""
try:
# some paranoid checks..
assert lines[0].startswith("NLLOC ")
assert lines[-1].startswith("END_NLLOC")
for line in lines[1:-1]:
assert not line.startswith("NLLOC ")
assert not line.startswith("END_NLLOC")
except Exception:
msg = ("This should not have happened, please report this as a bug at "
"https://github.com/obspy/obspy/issues.")
raise Exception(msg)
indices_phases = [None, None]
for i, line in enumerate(lines):
if line.startswith("PHASE "):
indices_phases[0] = i
elif line.startswith("END_PHASE"):
indices_phases[1] = i
# extract PHASES lines (if any)
if any(indices_phases):
if not all(indices_phases):
msg = ("NLLOC HYP file seems corrupt, 'PHASE' block is corrupt.")
raise RuntimeError(msg)
i1, i2 = indices_phases
lines, phases_lines = lines[:i1] + lines[i2 + 1:], lines[i1 + 1:i2]
else:
phases_lines = []
lines = dict([line.split(None, 1) for line in lines[:-1]])
line = lines["SIGNATURE"]
line = line.rstrip().split('"')[1]
signature, version, date, time = line.rsplit(" ", 3)
# new NLLoc > 6.0 seems to add prefix 'run:' before date
if date.startswith('run:'):
date = date[4:]
signature = signature.strip()
creation_time = UTCDateTime.strptime(date + time, str("%d%b%Y%Hh%Mm%S"))
if coordinate_converter:
# maximum likelihood origin location in km info line
line = lines["HYPOCENTER"]
x, y, z = coordinate_converter(*map(float, line.split()[1:7:2]))
else:
# maximum likelihood origin location lon lat info line
line = lines["GEOGRAPHIC"]
y, x, z = map(float, line.split()[8:13:2])
# maximum likelihood origin time info line
line = lines["GEOGRAPHIC"]
year, mon, day, hour, min = map(int, line.split()[1:6])
seconds = float(line.split()[6])
time = UTCDateTime(year, mon, day, hour, min, seconds, strict=False)
# distribution statistics line
line = lines["STATISTICS"]
covariance_xx = float(line.split()[7])
covariance_yy = float(line.split()[13])
covariance_zz = float(line.split()[17])
stats_info_string = str(
"Note: Depth/Latitude/Longitude errors are calculated from covariance "
"matrix as 1D marginal (Lon/Lat errors as great circle degrees) "
"while OriginUncertainty min/max horizontal errors are calculated "
"from 2D error ellipsoid and are therefore seemingly higher compared "
"to 1D errors. Error estimates can be reconstructed from the "
"following original NonLinLoc error statistics line:\nSTATISTICS " +
lines["STATISTICS"])
# goto location quality info line
line = lines["QML_OriginQuality"].split()
(assoc_phase_count, used_phase_count, assoc_station_count,
used_station_count, depth_phase_count) = map(int, line[1:11:2])
stderr, az_gap, sec_az_gap = map(float, line[11:17:2])
gt_level = line[17]
min_dist, max_dist, med_dist = map(float, line[19:25:2])
# goto location quality info line
line = lines["QML_OriginUncertainty"]
if "COMMENT" in lines:
comment = lines["COMMENT"].strip()
comment = comment.strip('\'"')
comment = comment.strip()
hor_unc, min_hor_unc, max_hor_unc, hor_unc_azim = \
map(float, line.split()[1:9:2])
# assign origin info
event = Event()
o = Origin()
event.origins = [o]
event.preferred_origin_id = o.resource_id
o.origin_uncertainty = OriginUncertainty()
o.quality = OriginQuality()
ou = o.origin_uncertainty
oq = o.quality
o.comments.append(Comment(text=stats_info_string, force_resource_id=False))
event.comments.append(Comment(text=comment, force_resource_id=False))
# SIGNATURE field's first item is LOCSIG, which is supposed to be
# 'Identification of an individual, institiution or other entity'
# according to
# http://alomax.free.fr/nlloc/soft6.00/control.html#_NLLoc_locsig_
# so use it as author in creation info
event.creation_info = CreationInfo(creation_time=creation_time,
version=version,
author=signature)
o.creation_info = CreationInfo(creation_time=creation_time,
version=version,
author=signature)
# negative values can appear on diagonal of covariance matrix due to a
# precision problem in NLLoc implementation when location coordinates are
# large compared to the covariances.
o.longitude = x
try:
o.longitude_errors.uncertainty = kilometer2degrees(sqrt(covariance_xx))
except ValueError:
if covariance_xx < 0:
msg = ("Negative value in XX value of covariance matrix, not "
"setting longitude error (epicentral uncertainties will "
"still be set in origin uncertainty).")
warnings.warn(msg)
else:
raise
o.latitude = y
try:
o.latitude_errors.uncertainty = kilometer2degrees(sqrt(covariance_yy))
except ValueError:
if covariance_yy < 0:
msg = ("Negative value in YY value of covariance matrix, not "
"setting longitude error (epicentral uncertainties will "
"still be set in origin uncertainty).")
warnings.warn(msg)
else:
raise
o.depth = z * 1e3 # meters!
o.depth_errors.uncertainty = sqrt(covariance_zz) * 1e3 # meters!
o.depth_errors.confidence_level = 68
o.depth_type = str("from location")
o.time = time
ou.horizontal_uncertainty = hor_unc
ou.min_horizontal_uncertainty = min_hor_unc
ou.max_horizontal_uncertainty = max_hor_unc
# values of -1 seem to be used for unset values, set to None
for field in ("horizontal_uncertainty", "min_horizontal_uncertainty",
"max_horizontal_uncertainty"):
if ou.get(field, -1) == -1:
ou[field] = None
else:
ou[field] *= 1e3 # meters!
ou.azimuth_max_horizontal_uncertainty = hor_unc_azim
ou.preferred_description = str("uncertainty ellipse")
ou.confidence_level = 68 # NonLinLoc in general uses 1-sigma (68%) level
oq.standard_error = stderr
oq.azimuthal_gap = az_gap
oq.secondary_azimuthal_gap = sec_az_gap
oq.used_phase_count = used_phase_count
oq.used_station_count = used_station_count
oq.associated_phase_count = assoc_phase_count
oq.associated_station_count = assoc_station_count
oq.depth_phase_count = depth_phase_count
oq.ground_truth_level = gt_level
oq.minimum_distance = kilometer2degrees(min_dist)
oq.maximum_distance = kilometer2degrees(max_dist)
oq.median_distance = kilometer2degrees(med_dist)
# go through all phase info lines
for line in phases_lines:
line = line.split()
arrival = Arrival()
o.arrivals.append(arrival)
station = str(line[0])
phase = str(line[4])
arrival.phase = phase
arrival.distance = kilometer2degrees(float(line[21]))
arrival.azimuth = float(line[23])
arrival.takeoff_angle = float(line[24])
arrival.time_residual = float(line[16])
arrival.time_weight = float(line[17])
pick = Pick()
# network codes are not used by NonLinLoc, so they can not be known
# when reading the .hyp file.. to conform with QuakeML standard set an
# empty network code
wid = WaveformStreamID(network_code="", station_code=station)
# have to split this into ints for overflow to work correctly
date, hourmin, sec = map(str, line[6:9])
ymd = [int(date[:4]), int(date[4:6]), int(date[6:8])]
hm = [int(hourmin[:2]), int(hourmin[2:4])]
t = UTCDateTime(*(ymd + hm), strict=False) + float(sec)
pick.waveform_id = wid
pick.time = t
pick.time_errors.uncertainty = float(line[10])
pick.phase_hint = phase
pick.onset = ONSETS.get(line[3].lower(), None)
pick.polarity = POLARITIES.get(line[5].lower(), None)
# try to determine original pick for each arrival
for pick_ in original_picks:
wid = pick_.waveform_id
if station == wid.station_code and phase == pick_.phase_hint:
pick = pick_
break
else:
# warn if original picks were specified and we could not associate
# the arrival correctly
if original_picks:
msg = ("Could not determine corresponding original pick for "
"arrival. "
"Falling back to pick information in NonLinLoc "
"hypocenter-phase file.")
warnings.warn(msg)
event.picks.append(pick)
arrival.pick_id = pick.resource_id
event.scope_resource_ids()
return event
def setEventData(eventParser, arrivals, count):
global originCount
global eventCount
global pickCount
creation_info = CreationInfo(
author='niket_engdahl_parser',
creation_time=UTCDateTime(),
agency_uri=ResourceIdentifier(id='smi:engdahl.ga.gov.au/ga-engdahl'),
agency_id='ga-engdahl')
# magnitudeSurface = Magnitude(resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/'+str(originCount)+'#netMag.Ms'),
# mag=eventParser.ms,
# magnitude_type='Ms',
# origin_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/'+str(originCount)),
# azimuthal_gap=eventParser.openaz2,
# creation_info=creation_info)
origin = Origin(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount)),
time=UTCDateTime(int(str(2000 + int(eventParser.iyr))),
int(eventParser.mon), int(eventParser.iday),
int(eventParser.ihr), int(eventParser.min),
int(eventParser.sec.split('.')[0]),
int(eventParser.sec.split('.')[1] + '0')),
longitude=eventParser.glon,
latitude=eventParser.glat,
depth=float(eventParser.depth) *
1000, # engdahl files report kms, obspy expects m
depth_errors=eventParser.sedep,
method_id=ResourceIdentifier(id='EHB'),
earth_model_id=ResourceIdentifier(id='ak135'),
quality=OriginQuality(associated_phase_count=len(arrivals),
used_phase_count=len(arrivals),
standard_error=eventParser.se,
azimuthal_gap=eventParser.openaz2),
evaluation_mode='automatic',
creation_info=creation_info)
magnitude = Magnitude(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount) + '#netMag.Mb'),
mag=eventParser.mb,
magnitude_type='Mb',
origin_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/origin/' +
str(originCount)),
azimuthal_gap=eventParser.openaz1,
creation_info=creation_info)
originCount += 1
pickList = []
arrivalList = []
pPhaseArrival = None
for arrParser in arrivals:
pickOnset = None
pol = None
if arrParser.year and arrParser.month and arrParser.day and arrParser.station:
pPhaseArrival = arrParser
else:
arrParser.year = pPhaseArrival.year
arrParser.day = pPhaseArrival.day
arrParser.month = pPhaseArrival.month
arrParser.station = pPhaseArrival.station
arrParser.delta = pPhaseArrival.delta
arrParser.dtdd = pPhaseArrival.dtdd
arrParser.backaz = pPhaseArrival.backaz
arrParser.focalDip = pPhaseArrival.focalDip
arrParser.angleAzimuth = pPhaseArrival.angleAzimuth
if arrParser.phase1 == 'LR' or arrParser.phase2 == 'LR' or arrParser.hour == '24':
continue
if arrParser.phase1.startswith('i'):
pickOnset = PickOnset.impulsive
if arrParser.fm == '+':
pol = PickPolarity.positive
elif arrParser.fm == '-':
pol = PickPolarity.negative
elif arrParser.phase1.startswith('e'):
pickOnset = PickOnset.emergent
pick = Pick(
resource_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/pick/' +
str(pickCount)),
time=UTCDateTime(int(str(2000 + int(arrParser.year))),
int(arrParser.month), int(arrParser.day),
int(arrParser.hour), int(arrParser.minute),
int(arrParser.second.split('.')[0]),
int(arrParser.second.split('.')[1] + '0')),
waveform_id=WaveformStreamID(network_code='',
station_code=arrParser.station,
channel_code='BHZ'),
methodID=ResourceIdentifier('STA/LTA'),
backazimuth=arrParser.backaz if arrParser.backaz else None,
onset=pickOnset,
phase_hint=arrParser.phase,
polarity=pol,
evaluation_mode='automatic',
# TO-DO
comment='populate all the remaining fields here as key value',
creation_info=creation_info)
if not arrParser.backaz:
print "arrParser.backaz is empty. printing the arrParser for debugging"
pickCount += 1
pickList.append(pick)
arrival = Arrival(
pick_id=ResourceIdentifier(id='smi:engdahl.ga.gov.au/pick/' +
str(pickCount - 1)),
phase=arrParser.phase if arrParser.phase else None,
azimuth=arrParser.backaz if arrParser.backaz else None,
distance=arrParser.delta if arrParser.delta else None,
# if the * has some significance, it should be accounted for. ignoring for now.
time_residual=arrParser.residual.rstrip('*'),
time_weight=arrParser.wgt if arrParser.wgt else None,
backazimuth_weight=arrParser.wgt if arrParser.wgt else None)
arrivalList.append(arrival)
if not arrParser.wgt:
print "arrParser.wgt is empty. printing the arrParser for debugging"
# pprint.pprint(arrParser)
origin.arrivals = arrivalList
event = Event(resource_id=ResourceIdentifier(
id='smi:engdahl.ga.gov.au/event/' + str(eventCount)),
creation_info=creation_info,
event_type='earthquake')
eventCount += 1
event.picks = pickList
event.origins = [
origin,
]
event.magnitudes = [
magnitude,
]
event.preferred_origin_id = origin.resource_id
event.preferred_magnitude_id = magnitude.resource_id
return event
def _internal_read_single_scardec(buf):
"""
Reads a single SCARDEC file to a :class:`~obspy.core.event.Catalog`
object.
:param buf: File to read.
:type buf: Open file or open file like object.
"""
# The first line encodes the origin time and epicenter
line = buf.readline()
origin_time = line.strip().split()[:6]
values = list(map(int, origin_time[:-1])) + \
[float(origin_time[-1])]
try:
origin_time = UTCDateTime(*values)
except (TypeError, ValueError):
warnings.warn("Could not determine origin time from line: %s. Will "
"be set to zero." % line)
origin_time = UTCDateTime(0)
line = line.split()[6:]
latitude, longitude = map(float, line[:2])
# The second line encodes depth and the two focal mechanisms
line = buf.readline()
line = line.split()
# First three values are depth, scalar moment (in Nm) and moment magnitude
depth, scalar_moment, moment_mag = map(float, line[0:3])
# depth is in km in SCARDEC files
depth *= 1e3
# Next six values are strike, dip, rake for both planes
strike1, dip1, rake1 = map(float, line[3:6])
strike2, dip2, rake2 = map(float, line[6:9])
# The rest of the file is the moment rate function
# In each line: time (sec), moment rate (Nm/sec)
stf_time = []
stf_mr = []
for line in buf:
stf_time.append(float(line.split()[0]))
stf_mr.append(float(line.split()[1]))
# Normalize the source time function
stf_mr = np.array(stf_mr)
stf_mr /= scalar_moment
# Calculate the time step
dt = np.mean(np.diff(stf_time))
# Calculate the stf offset (time of first sample wrt to origin time)
offset = stf_time[0]
# event name is set to generic value for now
event_name = 'SCARDEC_event'
cmt_origin = Origin(
resource_id=_get_resource_id(event_name, "origin", tag="cmt"),
time=origin_time,
longitude=longitude,
latitude=latitude,
depth=depth,
origin_type="centroid",
region=_fe.get_region(longitude=longitude,
latitude=latitude)
)
cmt_mag = Magnitude(
resource_id=_get_resource_id(event_name, "magnitude", tag="mw"),
mag=moment_mag,
magnitude_type="mw",
origin_id=cmt_origin.resource_id
)
nod1 = NodalPlane(strike=strike1, dip=dip1, rake=rake1)
nod2 = NodalPlane(strike=strike2, dip=dip2, rake=rake2)
nod = NodalPlanes(nodal_plane_1=nod1, nodal_plane_2=nod2)
foc_mec = FocalMechanism(
resource_id=_get_resource_id(event_name, "focal_mechanism"),
nodal_planes=nod
)
dip1 *= np.pi / 180.
rake1 *= np.pi / 180.
strike1 *= np.pi / 180.
mxx = - scalar_moment * ((np.sin(dip1) * np.cos(rake1) *
np.sin(2 * strike1)) +
(np.sin(2 * dip1) * np.sin(rake1) *
np.sin(2 * strike1)))
mxy = scalar_moment * ((np.sin(dip1) * np.cos(rake1) *
np.cos(2 * strike1)) +
(np.sin(2 * dip1) * np.sin(rake1) *
np.sin(2 * strike1) * 0.5))
myy = scalar_moment * ((np.sin(dip1) * np.cos(rake1) *
np.sin(2 * strike1)) -
(np.sin(2 * dip1) * np.sin(rake1) *
np.cos(2 * strike1)))
mxz = - scalar_moment * ((np.cos(dip1) * np.cos(rake1) *
np.cos(strike1)) +
(np.cos(2 * dip1) * np.sin(rake1) *
np.sin(strike1)))
myz = - scalar_moment * ((np.cos(dip1) * np.cos(rake1) *
np.sin(strike1)) -
(np.cos(2 * dip1) * np.sin(rake1) *
np.cos(strike1)))
mzz = scalar_moment * (np.sin(2 * dip1) * np.sin(rake1))
tensor = Tensor(m_rr=mxx, m_tt=myy, m_pp=mzz, m_rt=mxy, m_rp=mxz, m_tp=myz)
cm = [Comment(text="Basis system: North,East,Down \
(Jost and Herrmann 1989)")]
cm[0].resource_id = _get_resource_id(event_name, 'comment', 'mt')
cm.append(Comment(text="MT derived from focal mechanism, therefore \
constrained to pure double couple.",
force_resource_id=False))
# Write moment rate function
extra = {'moment_rate': {'value': stf_mr,
'namespace': r"http://test.org/xmlns/0.1"},
'dt': {'value': dt,
'namespace': r"http://test.org/xmlns/0.1"},
'offset': {'value': offset,
'namespace': r"http://test.org/xmlns/0.1"}
}
# Source time function
stf = SourceTimeFunction(type="unknown")
stf.extra = extra
mt = MomentTensor(
resource_id=_get_resource_id(event_name, "moment_tensor"),
derived_origin_id=cmt_origin.resource_id,
moment_magnitude_id=cmt_mag.resource_id,
scalar_moment=scalar_moment,
tensor=tensor,
source_time_function=stf,
comments=cm
)
# Assemble everything.
foc_mec.moment_tensor = mt
ev = Event(resource_id=_get_resource_id(event_name, "event"),
event_type="earthquake")
ev.event_descriptions.append(EventDescription(text=event_name,
type="earthquake name"))
ev.comments.append(Comment(
text="Hypocenter catalog: SCARDEC",
force_resource_id=False))
ev.origins.append(cmt_origin)
ev.magnitudes.append(cmt_mag)
ev.focal_mechanisms.append(foc_mec)
# Set the preferred items.
ev.preferred_origin_id = cmt_origin.resource_id.id
ev.preferred_magnitude_id = cmt_mag.resource_id.id
ev.preferred_focal_mechanism_id = foc_mec.resource_id.id
return ev
def _read_ndk(filename, *args, **kwargs): # @UnusedVariable
"""
Reads an NDK file to a :class:`~obspy.core.event.Catalog` object.
:param filename: File or file-like object in text mode.
"""
# Read the whole file at once. While an iterator would be more efficient
# the largest NDK file out in the wild is 13.7 MB so it does not matter
# much.
if not hasattr(filename, "read"):
# Check if it exists, otherwise assume its a string.
try:
with open(filename, "rt") as fh:
data = fh.read()
except:
try:
data = filename.decode()
except:
data = str(filename)
data = data.strip()
else:
data = filename.read()
if hasattr(data, "decode"):
data = data.decode()
# Create iterator that yields lines.
def lines_iter():
prev_line = -1
while True:
next_line = data.find("\n", prev_line + 1)
if next_line < 0:
break
yield data[prev_line + 1: next_line]
prev_line = next_line
if len(data) > prev_line + 1:
yield data[prev_line + 1:]
# Use one Flinn Engdahl object for all region determinations.
fe = FlinnEngdahl()
cat = Catalog(resource_id=_get_resource_id("catalog", str(uuid.uuid4())))
# Loop over 5 lines at once.
for _i, lines in enumerate(itertools.zip_longest(*[lines_iter()] * 5)):
if None in lines:
msg = "Skipped last %i lines. Not a multiple of 5 lines." % (
lines.count(None))
warnings.warn(msg, ObsPyNDKWarning)
continue
# Parse the lines to a human readable dictionary.
try:
record = _read_lines(*lines)
except (ValueError, ObsPyNDKException):
exc = traceback.format_exc()
msg = (
"Could not parse event %i (faulty file?). Will be "
"skipped. Lines of the event:\n"
"\t%s\n"
"%s") % (_i + 1, "\n\t".join(lines), exc)
warnings.warn(msg, ObsPyNDKWarning)
continue
# Use one creation info for essentially every item.
creation_info = CreationInfo(
agency_id="GCMT",
version=record["version_code"]
)
# Use the ObsPy Flinn Engdahl region determiner as the region in the
# NDK files is oftentimes trimmed.
region = fe.get_region(record["centroid_longitude"],
record["centroid_latitude"])
# Create an event object.
event = Event(
force_resource_id=False,
event_type="earthquake",
event_type_certainty="known",
event_descriptions=[
EventDescription(text=region, type="Flinn-Engdahl region"),
EventDescription(text=record["cmt_event_name"],
type="earthquake name")
]
)
# Assemble the time for the reference origin.
try:
time = _parse_date_time(record["date"], record["time"])
except ObsPyNDKException:
msg = ("Invalid time in event %i. '%s' and '%s' cannot be "
"assembled to a valid time. Event will be skipped.") % \
(_i + 1, record["date"], record["time"])
warnings.warn(msg, ObsPyNDKWarning)
continue
# Create two origins, one with the reference latitude/longitude and
# one with the centroidal values.
ref_origin = Origin(
force_resource_id=False,
time=time,
longitude=record["hypo_lng"],
latitude=record["hypo_lat"],
# Convert to m.
depth=record["hypo_depth_in_km"] * 1000.0,
origin_type="hypocenter",
comments=[Comment(text="Hypocenter catalog: %s" %
record["hypocenter_reference_catalog"],
force_resource_id=False)]
)
ref_origin.comments[0].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="ref_origin")
ref_origin.resource_id = _get_resource_id(record["cmt_event_name"],
"origin", tag="reforigin")
cmt_origin = Origin(
force_resource_id=False,
longitude=record["centroid_longitude"],
longitude_errors={
"uncertainty": record["centroid_longitude_error"]},
latitude=record["centroid_latitude"],
latitude_errors={
"uncertainty": record["centroid_latitude_error"]},
# Convert to m.
depth=record["centroid_depth_in_km"] * 1000.0,
depth_errors={
"uncertainty": record["centroid_depth_in_km_error"] * 1000},
time=ref_origin["time"] + record["centroid_time"],
time_errors={"uncertainty": record["centroid_time_error"]},
depth_type=record["type_of_centroid_depth"],
origin_type="centroid",
time_fixed=False,
epicenter_fixed=False,
creation_info=creation_info.copy()
)
cmt_origin.resource_id = _get_resource_id(record["cmt_event_name"],
"origin",
tag="cmtorigin")
event.origins = [ref_origin, cmt_origin]
event.preferred_origin_id = cmt_origin.resource_id.id
# Create the magnitude object.
mag = Magnitude(
force_resource_id=False,
mag=round(record["Mw"], 2),
magnitude_type="Mwc",
origin_id=cmt_origin.resource_id,
creation_info=creation_info.copy()
)
mag.resource_id = _get_resource_id(record["cmt_event_name"],
"magnitude", tag="moment_mag")
event.magnitudes = [mag]
event.preferred_magnitude_id = mag.resource_id.id
# Add the reported mb, MS magnitudes as additional magnitude objects.
event.magnitudes.append(Magnitude(
force_resource_id=False,
mag=record["mb"],
magnitude_type="mb",
comments=[Comment(
force_resource_id=False,
text="Reported magnitude in NDK file. Most likely 'mb'."
)]
))
event.magnitudes[-1].comments[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="mb_magnitude")
event.magnitudes[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "magnitude", tag="mb")
event.magnitudes.append(Magnitude(
force_resource_id=False,
mag=record["MS"],
magnitude_type="MS",
comments=[Comment(
force_resource_id=False,
text="Reported magnitude in NDK file. Most likely 'MS'."
)]
))
event.magnitudes[-1].comments[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="MS_magnitude")
event.magnitudes[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "magnitude", tag="MS")
# Take care of the moment tensor.
tensor = Tensor(
m_rr=record["m_rr"],
m_rr_errors={"uncertainty": record["m_rr_error"]},
m_pp=record["m_pp"],
m_pp_errors={"uncertainty": record["m_pp_error"]},
m_tt=record["m_tt"],
m_tt_errors={"uncertainty": record["m_tt_error"]},
m_rt=record["m_rt"],
m_rt_errors={"uncertainty": record["m_rt_error"]},
m_rp=record["m_rp"],
m_rp_errors={"uncertainty": record["m_rp_error"]},
m_tp=record["m_tp"],
m_tp_errors={"uncertainty": record["m_tp_error"]},
creation_info=creation_info.copy()
)
mt = MomentTensor(
force_resource_id=False,
scalar_moment=record["scalar_moment"],
tensor=tensor,
data_used=[DataUsed(**i) for i in record["data_used"]],
inversion_type=record["source_type"],
source_time_function=SourceTimeFunction(
type=record["moment_rate_type"],
duration=record["moment_rate_duration"]
),
derived_origin_id=cmt_origin.resource_id,
creation_info=creation_info.copy()
)
mt.resource_id = _get_resource_id(record["cmt_event_name"],
"momenttensor")
axis = [Axis(**i) for i in record["principal_axis"]]
focmec = FocalMechanism(
force_resource_id=False,
moment_tensor=mt,
principal_axes=PrincipalAxes(
# The ordering is the same as for the IRIS SPUD service and
# from a website of the Saint Louis University Earthquake
# center so it should be correct.
t_axis=axis[0],
p_axis=axis[2],
n_axis=axis[1]
),
nodal_planes=NodalPlanes(
nodal_plane_1=NodalPlane(**record["nodal_plane_1"]),
nodal_plane_2=NodalPlane(**record["nodal_plane_2"])
),
comments=[
Comment(force_resource_id=False,
text="CMT Analysis Type: %s" %
record["cmt_type"].capitalize()),
Comment(force_resource_id=False,
text="CMT Timestamp: %s" %
record["cmt_timestamp"])],
creation_info=creation_info.copy()
)
focmec.comments[0].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="cmt_type")
focmec.comments[1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="cmt_timestamp")
focmec.resource_id = _get_resource_id(record["cmt_event_name"],
"focal_mechanism")
event.focal_mechanisms = [focmec]
event.preferred_focal_mechanism_id = focmec.resource_id.id
# Set at end to avoid duplicate resource id warning.
event.resource_id = _get_resource_id(record["cmt_event_name"],
"event")
cat.append(event)
if len(cat) == 0:
msg = "No valid events found in NDK file."
raise ObsPyNDKException(msg)
return cat
def readheader(sfile):
"""
Read header information from a seisan nordic format S-file.
Returns an obspy.core.event.Catalog type: note this changed for version \
0.1.0 from the inbuilt class types.
:type sfile: str
:param sfile: Path to the s-file
:returns: :class: obspy.core.event.Event
>>> event = readheader('eqcorrscan/tests/test_data/REA/TEST_/' +
... '01-0411-15L.S201309')
>>> print(event.origins[0].time)
2013-09-01T04:11:15.700000Z
"""
import warnings
from obspy.core.event import Event, Origin, Magnitude, Comment
from obspy.core.event import EventDescription, CreationInfo
f = open(sfile, 'r')
# Base populate to allow for empty parts of file
new_event = Event()
topline = f.readline()
if not len(topline.rstrip()) == 80:
raise IOError('s-file has a corrupt header, not 80 char long')
f.seek(0)
for line in f:
if line[79] in [' ', '1']:
topline = line
break
if line[79] == '7':
raise IOError('No header found, corrupt s-file?')
try:
sfile_seconds = int(topline[16:18])
if sfile_seconds == 60:
sfile_seconds = 0
add_seconds = 60
else:
add_seconds = 0
new_event.origins.append(Origin())
new_event.origins[0].time = UTCDateTime(int(topline[1:5]),
int(topline[6:8]),
int(topline[8:10]),
int(topline[11:13]),
int(topline[13:15]),
sfile_seconds,
int(topline[19:20]) *
100000)\
+ add_seconds
except:
warnings.warn("Couldn't read a date from sfile: " + sfile)
new_event.origins.append(Origin(time=UTCDateTime(0)))
# new_event.loc_mod_ind=topline[20]
new_event.event_descriptions.append(EventDescription())
new_event.event_descriptions[0].text = topline[21:23]
# new_event.ev_id=topline[22]
if not _float_conv(topline[23:30]) == 999:
new_event.origins[0].latitude = _float_conv(topline[23:30])
new_event.origins[0].longitude = _float_conv(topline[31:38])
new_event.origins[0].depth = _float_conv(topline[39:43]) * 1000
# else:
# # The origin 'requires' a lat & long
# new_event.origins[0].latitude = float('NaN')
# new_event.origins[0].longitude = float('NaN')
# new_event.origins[0].depth = float('NaN')
# new_event.depth_ind = topline[44]
# new_event.loc_ind = topline[45]
new_event.creation_info = CreationInfo(agency_id=topline[45:48].strip())
ksta = Comment(text='Number of stations=' + topline[49:51].strip())
new_event.origins[0].comments.append(ksta)
# new_event.origins[0].nsta??? = _int_conv(topline[49:51])
if not _float_conv(topline[51:55]) == 999:
new_event.origins[0].time_errors['Time_Residual_RMS'] = \
_float_conv(topline[51:55])
# Read in magnitudes if they are there.
if len(topline[59].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[0].mag = _float_conv(topline[56:59])
new_event.magnitudes[0].magnitude_type = topline[59]
new_event.magnitudes[0].creation_info = \
CreationInfo(agency_id=topline[60:63].strip())
new_event.magnitudes[0].origin_id = new_event.origins[0].\
resource_id
if len(topline[67].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[1].mag = _float_conv(topline[64:67])
new_event.magnitudes[1].magnitude_type = topline[67]
new_event.magnitudes[1].creation_info = \
CreationInfo(agency_id=topline[68:71].strip())
new_event.magnitudes[1].origin_id = new_event.origins[0].\
resource_id
if len(topline[75].strip()) > 0:
new_event.magnitudes.append(Magnitude())
new_event.magnitudes[2].mag = _float_conv(topline[72:75])
new_event.magnitudes[2].magnitude_type = topline[75]
new_event.magnitudes[2].creation_info = \
CreationInfo(agency_id=topline[76:79].strip())
new_event.magnitudes[2].origin_id = new_event.origins[0].\
resource_id
f.close()
# convert the nordic notation of magnitude to more general notation
for _magnitude in new_event.magnitudes:
_magnitude.magnitude_type = _nortoevmag(_magnitude.magnitude_type)
# Set the useful things like preferred magnitude and preferred origin
new_event.preferred_origin_id = str(new_event.origins[0].resource_id)
if len(new_event.magnitudes) > 1:
try:
# Select moment first, then local, then
mag_filter = [
'MW', 'Mw', 'ML', 'Ml', 'MB', 'Mb', 'MS', 'Ms', 'Mc', 'MC'
]
_magnitudes = [(m.magnitude_type, m.resource_id)
for m in new_event.magnitudes]
preferred_magnitude = sorted(_magnitudes,
key=lambda x: mag_filter.index(x[0]))
new_event.preferred_magnitude_id = str(preferred_magnitude[0][1])
except ValueError:
# If there is a magnitude not specified in filter
new_event.preferred_magnitude_id =\
str(new_event.magnitudes[0].resource_id)
elif len(new_event.magnitudes) == 1:
new_event.preferred_magnitude_id =\
str(new_event.magnitudes[0].resource_id)
return new_event
def _read_ndk(filename, *args, **kwargs): # @UnusedVariable
"""
Reads an NDK file to a :class:`~obspy.core.event.Catalog` object.
:param filename: File or file-like object in text mode.
"""
# Read the whole file at once. While an iterator would be more efficient
# the largest NDK file out in the wild is 13.7 MB so it does not matter
# much.
if not hasattr(filename, "read"):
# Check if it exists, otherwise assume its a string.
try:
with open(filename, "rt") as fh:
data = fh.read()
except Exception:
try:
data = filename.decode()
except Exception:
data = str(filename)
data = data.strip()
else:
data = filename.read()
if hasattr(data, "decode"):
data = data.decode()
# Create iterator that yields lines.
def lines_iter():
prev_line = -1
while True:
next_line = data.find("\n", prev_line + 1)
if next_line < 0:
break
yield data[prev_line + 1:next_line]
prev_line = next_line
if len(data) > prev_line + 1:
yield data[prev_line + 1:]
# Use one Flinn Engdahl object for all region determinations.
fe = FlinnEngdahl()
cat = Catalog(resource_id=_get_resource_id("catalog", str(uuid.uuid4())))
# Loop over 5 lines at once.
for _i, lines in enumerate(zip_longest(*[lines_iter()] * 5)):
if None in lines:
msg = "Skipped last %i lines. Not a multiple of 5 lines." % (
lines.count(None))
warnings.warn(msg, ObsPyNDKWarning)
continue
# Parse the lines to a human readable dictionary.
try:
record = _read_lines(*lines)
except (ValueError, ObsPyNDKException):
exc = traceback.format_exc()
msg = ("Could not parse event %i (faulty file?). Will be "
"skipped. Lines of the event:\n"
"\t%s\n"
"%s") % (_i + 1, "\n\t".join(lines), exc)
warnings.warn(msg, ObsPyNDKWarning)
continue
# Use one creation info for essentially every item.
creation_info = CreationInfo(agency_id="GCMT",
version=record["version_code"])
# Use the ObsPy Flinn Engdahl region determiner as the region in the
# NDK files is oftentimes trimmed.
region = fe.get_region(record["centroid_longitude"],
record["centroid_latitude"])
# Create an event object.
event = Event(force_resource_id=False,
event_type="earthquake",
event_type_certainty="known",
event_descriptions=[
EventDescription(text=region,
type="Flinn-Engdahl region"),
EventDescription(text=record["cmt_event_name"],
type="earthquake name")
])
# Assemble the time for the reference origin.
try:
time = _parse_date_time(record["date"], record["time"])
except ObsPyNDKException:
msg = ("Invalid time in event %i. '%s' and '%s' cannot be "
"assembled to a valid time. Event will be skipped.") % \
(_i + 1, record["date"], record["time"])
warnings.warn(msg, ObsPyNDKWarning)
continue
# Create two origins, one with the reference latitude/longitude and
# one with the centroidal values.
ref_origin = Origin(
force_resource_id=False,
time=time,
longitude=record["hypo_lng"],
latitude=record["hypo_lat"],
# Convert to m.
depth=record["hypo_depth_in_km"] * 1000.0,
origin_type="hypocenter",
comments=[
Comment(text="Hypocenter catalog: %s" %
record["hypocenter_reference_catalog"],
force_resource_id=False)
])
ref_origin.comments[0].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="ref_origin")
ref_origin.resource_id = _get_resource_id(record["cmt_event_name"],
"origin",
tag="reforigin")
cmt_origin = Origin(
force_resource_id=False,
longitude=record["centroid_longitude"],
longitude_errors={
"uncertainty": record["centroid_longitude_error"]
},
latitude=record["centroid_latitude"],
latitude_errors={"uncertainty": record["centroid_latitude_error"]},
# Convert to m.
depth=record["centroid_depth_in_km"] * 1000.0,
depth_errors={
"uncertainty": record["centroid_depth_in_km_error"] * 1000
},
time=ref_origin["time"] + record["centroid_time"],
time_errors={"uncertainty": record["centroid_time_error"]},
depth_type=record["type_of_centroid_depth"],
origin_type="centroid",
time_fixed=False,
epicenter_fixed=False,
creation_info=creation_info.copy())
cmt_origin.resource_id = _get_resource_id(record["cmt_event_name"],
"origin",
tag="cmtorigin")
event.origins = [ref_origin, cmt_origin]
event.preferred_origin_id = cmt_origin.resource_id.id
# Create the magnitude object.
mag = Magnitude(force_resource_id=False,
mag=round(record["Mw"], 2),
magnitude_type="Mwc",
origin_id=cmt_origin.resource_id,
creation_info=creation_info.copy())
mag.resource_id = _get_resource_id(record["cmt_event_name"],
"magnitude",
tag="moment_mag")
event.magnitudes = [mag]
event.preferred_magnitude_id = mag.resource_id.id
# Add the reported mb, MS magnitudes as additional magnitude objects.
event.magnitudes.append(
Magnitude(
force_resource_id=False,
mag=record["mb"],
magnitude_type="mb",
comments=[
Comment(
force_resource_id=False,
text="Reported magnitude in NDK file. Most likely 'mb'."
)
]))
event.magnitudes[-1].comments[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="mb_magnitude")
event.magnitudes[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "magnitude", tag="mb")
event.magnitudes.append(
Magnitude(
force_resource_id=False,
mag=record["MS"],
magnitude_type="MS",
comments=[
Comment(
force_resource_id=False,
text="Reported magnitude in NDK file. Most likely 'MS'."
)
]))
event.magnitudes[-1].comments[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="MS_magnitude")
event.magnitudes[-1].resource_id = _get_resource_id(
record["cmt_event_name"], "magnitude", tag="MS")
# Take care of the moment tensor.
tensor = Tensor(m_rr=record["m_rr"],
m_rr_errors={"uncertainty": record["m_rr_error"]},
m_pp=record["m_pp"],
m_pp_errors={"uncertainty": record["m_pp_error"]},
m_tt=record["m_tt"],
m_tt_errors={"uncertainty": record["m_tt_error"]},
m_rt=record["m_rt"],
m_rt_errors={"uncertainty": record["m_rt_error"]},
m_rp=record["m_rp"],
m_rp_errors={"uncertainty": record["m_rp_error"]},
m_tp=record["m_tp"],
m_tp_errors={"uncertainty": record["m_tp_error"]},
creation_info=creation_info.copy())
mt = MomentTensor(
force_resource_id=False,
scalar_moment=record["scalar_moment"],
tensor=tensor,
data_used=[DataUsed(**i) for i in record["data_used"]],
inversion_type=record["source_type"],
source_time_function=SourceTimeFunction(
type=record["moment_rate_type"],
duration=record["moment_rate_duration"]),
derived_origin_id=cmt_origin.resource_id,
creation_info=creation_info.copy())
mt.resource_id = _get_resource_id(record["cmt_event_name"],
"momenttensor")
axis = [Axis(**i) for i in record["principal_axis"]]
focmec = FocalMechanism(
force_resource_id=False,
moment_tensor=mt,
principal_axes=PrincipalAxes(
# The ordering is the same as for the IRIS SPUD service and
# from a website of the Saint Louis University Earthquake
# center so it should be correct.
t_axis=axis[0],
p_axis=axis[2],
n_axis=axis[1]),
nodal_planes=NodalPlanes(
nodal_plane_1=NodalPlane(**record["nodal_plane_1"]),
nodal_plane_2=NodalPlane(**record["nodal_plane_2"])),
comments=[
Comment(force_resource_id=False,
text="CMT Analysis Type: %s" %
record["cmt_type"].capitalize()),
Comment(force_resource_id=False,
text="CMT Timestamp: %s" % record["cmt_timestamp"])
],
creation_info=creation_info.copy())
focmec.comments[0].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="cmt_type")
focmec.comments[1].resource_id = _get_resource_id(
record["cmt_event_name"], "comment", tag="cmt_timestamp")
focmec.resource_id = _get_resource_id(record["cmt_event_name"],
"focal_mechanism")
event.focal_mechanisms = [focmec]
event.preferred_focal_mechanism_id = focmec.resource_id.id
# Set at end to avoid duplicate resource id warning.
event.resource_id = _get_resource_id(record["cmt_event_name"], "event")
cat.append(event)
if len(cat) == 0:
msg = "No valid events found in NDK file."
raise ObsPyNDKException(msg)
return cat
def _read_single_event(event_file, locate_dir, units, local_mag_ph):
"""
Parse an event file from QuakeMigrate into an obspy Event object.
Parameters
----------
event_file : `pathlib.Path` object
Path to .event file to read.
locate_dir : `pathlib.Path` object
Path to locate directory (contains "events", "picks" etc. directories).
units : {"km", "m"}
Grid projection coordinates for QM LUT (determines units of depths and
uncertainties in the .event files).
local_mag_ph : {"S", "P"}
Amplitude measurement used to calculate local magnitudes.
Returns
-------
event : `obspy.Event` object
Event object populated with all available information output by
:class:`~quakemigrate.signal.scan.locate()`, including event locations
and uncertainties, picks, and amplitudes and magnitudes if available.
"""
# Parse information from event file
event_info = pd.read_csv(event_file).iloc[0]
event_uid = str(event_info["EventID"])
# Set distance conversion factor (from units of QM LUT projection units).
if units == "km":
factor = 1e3
elif units == "m":
factor = 1
else:
raise AttributeError(f"units must be 'km' or 'm'; not {units}")
# Create event object to store origin and pick information
event = Event()
event.extra = AttribDict()
event.resource_id = str(event_info["EventID"])
event.creation_info = CreationInfo(author="QuakeMigrate",
version=quakemigrate.__version__)
# Add COA info to extra
event.extra.coa = {"value": event_info["COA"], "namespace": ns}
event.extra.coa_norm = {"value": event_info["COA_NORM"], "namespace": ns}
event.extra.trig_coa = {"value": event_info["TRIG_COA"], "namespace": ns}
event.extra.dec_coa = {"value": event_info["DEC_COA"], "namespace": ns}
event.extra.dec_coa_norm = {
"value": event_info["DEC_COA_NORM"],
"namespace": ns
}
# Determine location of cut waveform data - add to event object as a
# custom extra attribute.
mseed = locate_dir / "raw_cut_waveforms" / event_uid
event.extra.cut_waveforms_file = {
"value": str(mseed.with_suffix(".m").resolve()),
"namespace": ns
}
if (locate_dir / "real_cut_waveforms").exists():
mseed = locate_dir / "real_cut_waveforms" / event_uid
event.extra.real_cut_waveforms_file = {
"value": str(mseed.with_suffix(".m").resolve()),
"namespace": ns
}
if (locate_dir / "wa_cut_waveforms").exists():
mseed = locate_dir / "wa_cut_waveforms" / event_uid
event.extra.wa_cut_waveforms_file = {
"value": str(mseed.with_suffix(".m").resolve()),
"namespace": ns
}
# Create origin with spline location and set to preferred event origin.
origin = Origin()
origin.method_id = "spline"
origin.longitude = event_info["X"]
origin.latitude = event_info["Y"]
origin.depth = event_info["Z"] * factor
origin.time = UTCDateTime(event_info["DT"])
event.origins = [origin]
event.preferred_origin_id = origin.resource_id
# Create origin with gaussian location and associate with event
origin = Origin()
origin.method_id = "gaussian"
origin.longitude = event_info["GAU_X"]
origin.latitude = event_info["GAU_Y"]
origin.depth = event_info["GAU_Z"] * factor
origin.time = UTCDateTime(event_info["DT"])
event.origins.append(origin)
ouc = OriginUncertainty()
ce = ConfidenceEllipsoid()
ce.semi_major_axis_length = event_info["COV_ErrY"] * factor
ce.semi_intermediate_axis_length = event_info["COV_ErrX"] * factor
ce.semi_minor_axis_length = event_info["COV_ErrZ"] * factor
ce.major_axis_plunge = 0
ce.major_axis_azimuth = 0
ce.major_axis_rotation = 0
ouc.confidence_ellipsoid = ce
ouc.preferred_description = "confidence ellipsoid"
# Set uncertainties for both as the gaussian uncertainties
for origin in event.origins:
origin.longitude_errors.uncertainty = kilometer2degrees(
event_info["GAU_ErrX"] * factor / 1e3)
origin.latitude_errors.uncertainty = kilometer2degrees(
event_info["GAU_ErrY"] * factor / 1e3)
origin.depth_errors.uncertainty = event_info["GAU_ErrZ"] * factor
origin.origin_uncertainty = ouc
# Add OriginQuality info to each origin?
for origin in event.origins:
origin.origin_type = "hypocenter"
origin.evaluation_mode = "automatic"
# --- Handle picks file ---
pick_file = locate_dir / "picks" / event_uid
if pick_file.with_suffix(".picks").is_file():
picks = pd.read_csv(pick_file.with_suffix(".picks"))
else:
return None
for _, pickline in picks.iterrows():
station = str(pickline["Station"])
phase = str(pickline["Phase"])
wid = WaveformStreamID(network_code="", station_code=station)
for method in ["modelled", "autopick"]:
pick = Pick()
pick.extra = AttribDict()
pick.waveform_id = wid
pick.method_id = method
pick.phase_hint = phase
if method == "autopick" and str(pickline["PickTime"]) != "-1":
pick.time = UTCDateTime(pickline["PickTime"])
pick.time_errors.uncertainty = float(pickline["PickError"])
pick.extra.snr = {
"value": float(pickline["SNR"]),
"namespace": ns
}
elif method == "modelled":
pick.time = UTCDateTime(pickline["ModelledTime"])
else:
continue
event.picks.append(pick)
# --- Handle amplitudes file ---
amps_file = locate_dir / "amplitudes" / event_uid
if amps_file.with_suffix(".amps").is_file():
amps = pd.read_csv(amps_file.with_suffix(".amps"))
i = 0
for _, ampsline in amps.iterrows():
wid = WaveformStreamID(seed_string=ampsline["id"])
noise_amp = ampsline["Noise_amp"] / 1000 # mm to m
for phase in ["P_amp", "S_amp"]:
amp = Amplitude()
if pd.isna(ampsline[phase]):
continue
amp.generic_amplitude = ampsline[phase] / 1000 # mm to m
amp.generic_amplitude_errors.uncertainty = noise_amp
amp.unit = "m"
amp.type = "AML"
amp.method_id = phase
amp.period = 1 / ampsline[f"{phase[0]}_freq"]
amp.time_window = TimeWindow(
reference=UTCDateTime(ampsline[f"{phase[0]}_time"]))
# amp.pick_id = ?
amp.waveform_id = wid
# amp.filter_id = ?
amp.magnitude_hint = "ML"
amp.evaluation_mode = "automatic"
amp.extra = AttribDict()
try:
amp.extra.filter_gain = {
"value": ampsline[f"{phase[0]}_filter_gain"],
"namespace": ns
}
amp.extra.avg_amp = {
"value": ampsline[f"{phase[0]}_avg_amp"] / 1000, # m
"namespace": ns
}
except KeyError:
pass
if phase[0] == local_mag_ph and not pd.isna(ampsline["ML"]):
i += 1
stat_mag = StationMagnitude()
stat_mag.extra = AttribDict()
# stat_mag.origin_id = ? local_mag_loc
stat_mag.mag = ampsline["ML"]
stat_mag.mag_errors.uncertainty = ampsline["ML_Err"]
stat_mag.station_magnitude_type = "ML"
stat_mag.amplitude_id = amp.resource_id
stat_mag.extra.picked = {
"value": ampsline["is_picked"],
"namespace": ns
}
stat_mag.extra.epi_dist = {
"value": ampsline["epi_dist"],
"namespace": ns
}
stat_mag.extra.z_dist = {
"value": ampsline["z_dist"],
"namespace": ns
}
event.station_magnitudes.append(stat_mag)
event.amplitudes.append(amp)
mag = Magnitude()
mag.extra = AttribDict()
mag.mag = event_info["ML"]
mag.mag_errors.uncertainty = event_info["ML_Err"]
mag.magnitude_type = "ML"
# mag.origin_id = ?
mag.station_count = i
mag.evaluation_mode = "automatic"
mag.extra.r2 = {"value": event_info["ML_r2"], "namespace": ns}
event.magnitudes = [mag]
event.preferred_magnitude_id = mag.resource_id
return event
