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 _parseRecordAH(self, line, event):
"""
Parses the 'additional hypocenter' record AH
"""
date = line[2:10]
time = line[11:20]
#unused: hypocenter_quality = line[20]
latitude = self._float(line[21:27])
lat_type = line[27]
longitude = self._float(line[29:36])
lon_type = line[36]
#unused: preliminary_flag = line[37]
depth = self._float(line[38:43])
#unused: depth_quality = line[43]
standard_dev = self._floatUnused(line[44:48])
station_number = self._intUnused(line[48:51])
phase_number = self._intUnused(line[51:55])
source_code = line[56:60].strip()
evid = event.resource_id.id.split('/')[-1]
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin', evid, source_code.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo(agency_id=source_code)
origin.time = UTCDateTime(date + time)
origin.latitude = latitude * self._coordinateSign(lat_type)
origin.longitude = longitude * self._coordinateSign(lon_type)
origin.depth = depth * 1000
origin.depth_type = 'from location'
origin.quality = OriginQuality()
origin.quality.standard_error = standard_dev
origin.quality.used_station_count = station_number
origin.quality.used_phase_count = phase_number
origin.type = 'hypocenter'
event.origins.append(origin)
def _parse_record_ah(self, line, event):
"""
Parses the 'additional hypocenter' record AH
"""
date = line[2:10]
time = line[11:20]
# unused: hypocenter_quality = line[20]
latitude = self._float(line[21:27])
lat_type = line[27]
longitude = self._float(line[29:36])
lon_type = line[36]
# unused: preliminary_flag = line[37]
depth = self._float(line[38:43])
# unused: depth_quality = line[43]
standard_dev = self._float_unused(line[44:48])
station_number = self._int_unused(line[48:51])
phase_number = self._int_unused(line[51:55])
source_code = line[56:60].strip()
evid = event.resource_id.id.split('/')[-1]
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin', evid, source_code.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo(agency_id=source_code)
origin.time = UTCDateTime(date + time)
origin.latitude = latitude * self._coordinate_sign(lat_type)
origin.longitude = longitude * self._coordinate_sign(lon_type)
origin.depth = depth * 1000
origin.depth_type = 'from location'
origin.quality = OriginQuality()
origin.quality.standard_error = standard_dev
origin.quality.used_station_count = station_number
origin.quality.used_phase_count = phase_number
origin.origin_type = 'hypocenter'
event.origins.append(origin)
def _parse_record_hy(self, line):
"""
Parses the 'hypocenter' record HY
"""
date = line[2:10]
time = line[11:20]
# unused: location_quality = line[20]
latitude = self._float(line[21:27])
lat_type = line[27]
longitude = self._float(line[29:36])
lon_type = line[36]
depth = self._float(line[38:43])
# unused: depth_quality = line[43]
standard_dev = self._float(line[44:48])
station_number = self._int(line[48:51])
# unused: version_flag = line[51]
fe_region_number = line[52:55]
fe_region_name = self._decode_fe_region_number(fe_region_number)
source_code = line[55:60].strip()
event = Event()
# FIXME: a smarter way to define evid?
evid = date + time
res_id = '/'.join((res_id_prefix, 'event', evid))
event.resource_id = ResourceIdentifier(id=res_id)
description = EventDescription(
type='region name',
text=fe_region_name)
event.event_descriptions.append(description)
description = EventDescription(
type='Flinn-Engdahl region',
text=fe_region_number)
event.event_descriptions.append(description)
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin', evid))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo()
if source_code:
origin.creation_info.agency_id = source_code
else:
origin.creation_info.agency_id = 'USGS-NEIC'
res_id = '/'.join((res_id_prefix, 'earthmodel/ak135'))
origin.earth_model_id = ResourceIdentifier(id=res_id)
origin.time = UTCDateTime(date + time)
origin.latitude = latitude * self._coordinate_sign(lat_type)
origin.longitude = longitude * self._coordinate_sign(lon_type)
origin.depth = depth * 1000
origin.depth_type = 'from location'
origin.quality = OriginQuality()
origin.quality.associated_station_count = station_number
origin.quality.standard_error = standard_dev
# associated_phase_count can be incremented in records 'P ' and 'S '
origin.quality.associated_phase_count = 0
# depth_phase_count can be incremented in record 'S '
origin.quality.depth_phase_count = 0
origin.origin_type = 'hypocenter'
origin.region = fe_region_name
event.origins.append(origin)
return event
def _parse_record_hy(self, line):
"""
Parses the 'hypocenter' record HY
"""
date = line[2:10]
time = line[11:20]
# unused: location_quality = line[20]
latitude = self._float(line[21:27])
lat_type = line[27]
longitude = self._float(line[29:36])
lon_type = line[36]
depth = self._float(line[38:43])
# unused: depth_quality = line[43]
standard_dev = self._float(line[44:48])
station_number = self._int(line[48:51])
# unused: version_flag = line[51]
fe_region_number = line[52:55]
fe_region_name = self._decode_fe_region_number(fe_region_number)
source_code = line[55:60].strip()
event = Event()
# FIXME: a smarter way to define evid?
evid = date + time
res_id = '/'.join((res_id_prefix, 'event', evid))
event.resource_id = ResourceIdentifier(id=res_id)
description = EventDescription(
type='region name',
text=fe_region_name)
event.event_descriptions.append(description)
description = EventDescription(
type='Flinn-Engdahl region',
text=fe_region_number)
event.event_descriptions.append(description)
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin', evid))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo()
if source_code:
origin.creation_info.agency_id = source_code
else:
origin.creation_info.agency_id = 'USGS-NEIC'
res_id = '/'.join((res_id_prefix, 'earthmodel/ak135'))
origin.earth_model_id = ResourceIdentifier(id=res_id)
origin.time = UTCDateTime(date + time)
origin.latitude = latitude * self._coordinate_sign(lat_type)
origin.longitude = longitude * self._coordinate_sign(lon_type)
origin.depth = depth * 1000
origin.depth_type = 'from location'
origin.quality = OriginQuality()
origin.quality.associated_station_count = station_number
origin.quality.standard_error = standard_dev
# associated_phase_count can be incremented in records 'P ' and 'S '
origin.quality.associated_phase_count = 0
# depth_phase_count can be incremented in record 'S '
origin.quality.depth_phase_count = 0
origin.origin_type = 'hypocenter'
origin.region = fe_region_name
event.origins.append(origin)
return event
def _parseRecordDp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._intZero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + '.' + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == 'FX':
orig_time_stderr = 'Fixed'
else:
orig_time_stderr =\
self._floatWithFormat(orig_time_stderr, '2.1', scale)
centroid_latitude = self._floatWithFormat(line[17:21], '4.2')
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinateSign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == 'FX':
lat_stderr = 'Fixed'
else:
lat_stderr = self._floatWithFormat(lat_stderr, '3.2', scale)
centroid_longitude = self._floatWithFormat(line[25:30], '5.2')
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinateSign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == 'FX':
lon_stderr = 'Fixed'
else:
lon_stderr = self._floatWithFormat(lon_stderr, '3.2', scale)
centroid_depth = self._floatWithFormat(line[34:38], '4.1')
depth_stderr = line[38:40]
if depth_stderr == 'FX' or depth_stderr == 'BD':
depth_stderr = 'Fixed'
else:
depth_stderr = self._floatWithFormat(depth_stderr, '2.1', scale)
station_number = self._intZero(line[40:43])
component_number = self._intZero(line[43:46])
station_number2 = self._intZero(line[46:48])
component_number2 = self._intZero(line[48:51])
#unused: half_duration = self._floatWithFormat(line[51:54], '3.1')
moment = self._floatWithFormat(line[54:56], '2.1')
moment_stderr = self._floatWithFormat(line[56:58], '2.1')
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split('/')[-1]
#Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != '.':
origin = Origin()
res_id = '/'.join(
(res_id_prefix, 'origin', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info =\
CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime('%Y%m%d')
origin.time = UTCDateTime(date + centroid_origin_time)
#Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._storeUncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == 'Fixed' and lon_stderr == 'Fixed':
origin.epicenter_fixed = True
else:
self._storeUncertainty(origin.latitude_errors,
self._latErrToDeg(lat_stderr))
self._storeUncertainty(
origin.longitude_errors,
self._lonErrToDeg(lon_stderr, origin.latitude))
if depth_stderr == 'Fixed':
origin.depth_type = 'operator assigned'
else:
origin.depth_type = 'from location'
self._storeUncertainty(origin.depth_errors,
depth_stderr,
scale=1000)
quality = OriginQuality()
quality.used_station_count =\
station_number + station_number2
quality.used_phase_count =\
component_number + component_number2
origin.quality = quality
origin.type = 'centroid'
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = '/'.join(
(res_id_prefix, 'focalmechanism', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info =\
CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
#this is required for QuakeML validation:
res_id = '/'.join((res_id_prefix, 'no-origin'))
moment_tensor.derived_origin_id =\
ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = '/'.join(
(res_id_prefix, 'momenttensor', evid, source_contributor.lower(),
'mw' + computation_type.lower()))
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._storeUncertainty(moment_tensor.scalar_moment_errors,
moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == 'C':
res_id = '/'.join((res_id_prefix, 'methodID=CMT'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#CMT algorithm uses long-period body waves,
#very-long-period surface waves and
#intermediate period surface waves (since 2004
#for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = 'combined'
if computation_type == 'M':
res_id = '/'.join((res_id_prefix, 'methodID=moment_tensor'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: not sure which kind of data is used by
#"moment tensor" algorithm.
data_used.wave_type = 'unknown'
elif computation_type == 'B':
res_id = '/'.join((res_id_prefix, 'methodID=broadband_data'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: is 'combined' correct here?
data_used.wave_type = 'combined'
elif computation_type == 'F':
res_id = '/'.join((res_id_prefix, 'methodID=P-wave_first_motion'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = 'P waves'
elif computation_type == 'S':
res_id = '/'.join((res_id_prefix, 'methodID=scalar_moment'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
#FIXME: not sure which kind of data is used
#for scalar moment determination.
data_used.wave_type = 'unknown'
moment_tensor.data_used = data_used
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def _parse_first_line_origin(self, line, event, magnitudes):
"""
Parse the first line of origin data.
:type line: str
:param line: Line to parse.
:type event: :class:`~obspy.core.event.event.Event`
:param event: Event of the origin.
:type magnitudes: list of
:class:`~obspy.core.event.magnitude.Magnitude`
:param magnitudes: Store magnitudes in a list to keep
their positions.
:rtype: :class:`~obspy.core.event.origin.Origin`,
:class:`~obspy.core.event.resourceid.ResourceIdentifier`
:returns: Parsed origin or None, resource identifier of the
origin.
"""
magnitude_types = []
magnitude_values = []
magnitude_station_counts = []
fields = self.fields['line_1']
time_origin = line[fields['time']].strip()
time_fixed_flag = line[fields['time_fixf']].strip()
latitude = line[fields['lat']].strip()
longitude = line[fields['lon']].strip()
epicenter_fixed_flag = line[fields['epicenter_fixf']].strip()
depth = line[fields['depth']].strip()
depth_fixed_flag = line[fields['depth_fixf']].strip()
phase_count = line[fields['n_def']].strip()
station_count = line[fields['n_sta']].strip()
azimuthal_gap = line[fields['gap']].strip()
magnitude_types.append(line[fields['mag_type_1']].strip())
magnitude_values.append(line[fields['mag_1']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_1']].strip())
magnitude_types.append(line[fields['mag_type_2']].strip())
magnitude_values.append(line[fields['mag_2']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_2']].strip())
magnitude_types.append(line[fields['mag_type_3']].strip())
magnitude_values.append(line[fields['mag_3']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_3']].strip())
author = line[fields['author']].strip()
origin_id = line[fields['id']].strip()
origin = Origin()
origin.quality = OriginQuality()
try:
origin.time = UTCDateTime(time_origin.replace('/', '-'))
origin.latitude = float(latitude)
origin.longitude = float(longitude)
except (TypeError, ValueError):
self._warn('Missing origin data, skipping event')
return None, None
origin.time_fixed = time_fixed_flag.lower() == 'f'
origin.epicenter_fixed = epicenter_fixed_flag.lower() == 'f'
try:
# Convert value from km to m
origin.depth = float(depth) * 1000
except ValueError:
pass
try:
origin.depth_type = DEPTH_TYPES[depth_fixed_flag]
except KeyError:
origin.depth_type = OriginDepthType('from location')
try:
origin.quality.used_phase_count = int(phase_count)
origin.quality.associated_phase_count = int(phase_count)
except ValueError:
pass
try:
origin.quality.used_station_count = int(station_count)
origin.quality.associated_station_count = int(station_count)
except ValueError:
pass
try:
origin.quality.azimuthal_gap = float(azimuthal_gap)
except ValueError:
pass
self.author = author
origin.creation_info = self._get_creation_info()
public_id = "origin/%s" % origin_id
origin_res_id = self._get_res_id(public_id)
for i in range(3):
try:
magnitude = Magnitude()
magnitude.creation_info = self._get_creation_info()
magnitude.magnitude_type = magnitude_types[i]
magnitude.mag = float(magnitude_values[i])
magnitude.station_count = int(magnitude_station_counts[i])
magnitude.origin_id = origin_res_id
magnitudes.append(magnitude)
event.magnitudes.append(magnitude)
except ValueError:
# Magnitude can be empty but we need to keep the
# position between mag1, mag2 or mag3.
magnitudes.append(None)
return origin, origin_res_id
def read_nlloc_hyp(filename, coordinate_converter=None, picks=None, **kwargs):
"""
Reads a NonLinLoc Hypocenter-Phase file to a
:class:`~obspy.core.event.Catalog` object.
.. note::
Coordinate conversion from coordinate frame of NonLinLoc model files /
location run to WGS84 has to be specified explicitly by the user if
necessary.
.. note::
An example can be found on the :mod:`~obspy.nlloc` submodule front
page in the documentation pages.
:param filename: File or file-like object in text mode.
:type coordinate_converter: func
:param coordinate_converter: Function to convert (x, y, z)
coordinates of NonLinLoc output to geographical coordinates and depth
in meters (longitude, latitude, depth in kilometers).
If left `None` NonLinLoc (x, y, z) output is left unchanged (e.g. if
it is in geographical coordinates already like for NonLinLoc in
global mode).
The function should accept three arguments x, y, z and return a
tuple of three values (lon, lat, depth in kilometers).
:type picks: list of :class:`~obspy.core.event.Pick`
:param picks: Original picks used to generate the NonLinLoc location.
If provided, the output event will include the original picks and the
arrivals in the output origin will link to them correctly (with their
`pick_id` attribute). If not provided, the output event will include
(the rather basic) pick information that can be reconstructed from the
NonLinLoc hypocenter-phase file.
:rtype: :class:`~obspy.core.event.Catalog`
"""
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()
lines = data.splitlines()
# remember picks originally used in location, if provided
original_picks = picks
if original_picks is None:
original_picks = []
# determine indices of block start/end of the NLLOC output file
indices_hyp = [None, None]
indices_phases = [None, None]
for i, line in enumerate(lines):
if line.startswith("NLLOC "):
indices_hyp[0] = i
elif line.startswith("END_NLLOC"):
indices_hyp[1] = i
elif line.startswith("PHASE "):
indices_phases[0] = i
elif line.startswith("END_PHASE"):
indices_phases[1] = i
if any([i is None for i in indices_hyp]):
msg = ("NLLOC HYP file seems corrupt,"
" could not detect 'NLLOC' and 'END_NLLOC' lines.")
raise RuntimeError(msg)
# strip any other lines around NLLOC block
lines = lines[indices_hyp[0]:indices_hyp[1]]
# 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])
line = lines["SIGNATURE"]
line = line.rstrip().split('"')[1]
signature, version, date, time = line.rsplit(" ", 3)
creation_time = UTCDateTime().strptime(date + time, str("%d%b%Y%Hh%Mm%S"))
# maximum likelihood origin location info line
line = lines["HYPOCENTER"]
x, y, z = map(float, line.split()[1:7:2])
if coordinate_converter:
x, y, z = coordinate_converter(x, y, z)
# origin time info line
line = lines["GEOGRAPHIC"]
year, month, day, hour, minute = map(int, line.split()[1:6])
seconds = float(line.split()[6])
time = UTCDateTime(year, month, day, hour, minute, seconds)
# 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"]
hor_unc, min_hor_unc, max_hor_unc, hor_unc_azim = \
map(float, line.split()[1:9:2])
# assign origin info
event = Event()
cat = Catalog(events=[event])
o = Origin()
event.origins = [o]
o.origin_uncertainty = OriginUncertainty()
o.quality = OriginQuality()
ou = o.origin_uncertainty
oq = o.quality
o.comments.append(Comment(text=stats_info_string))
cat.creation_info.creation_time = UTCDateTime()
cat.creation_info.version = "ObsPy %s" % __version__
event.creation_info = CreationInfo(creation_time=creation_time,
version=version)
event.creation_info.version = version
o.creation_info = CreationInfo(creation_time=creation_time,
version=version)
# 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()
wid = WaveformStreamID(station_code=station)
date, hourmin, sec = map(str, line[6:9])
t = UTCDateTime().strptime(date + hourmin, "%Y%m%d%H%M") + 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
return cat
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_nlloc_hyp(filename, coordinate_converter=None, picks=None, **kwargs):
"""
Reads a NonLinLoc Hypocenter-Phase file to a
:class:`~obspy.core.event.Catalog` object.
.. note::
Coordinate conversion from coordinate frame of NonLinLoc model files /
location run to WGS84 has to be specified explicitly by the user if
necessary.
.. note::
An example can be found on the :mod:`~obspy.io.nlloc` submodule front
page in the documentation pages.
:param filename: File or file-like object in text mode.
:type coordinate_converter: func
:param coordinate_converter: Function to convert (x, y, z)
coordinates of NonLinLoc output to geographical coordinates and depth
in meters (longitude, latitude, depth in kilometers).
If left ``None``, NonLinLoc (x, y, z) output is left unchanged (e.g. if
it is in geographical coordinates already like for NonLinLoc in
global mode).
The function should accept three arguments x, y, z (each of type
:class:`numpy.ndarray`) and return a tuple of three
:class:`numpy.ndarray` (lon, lat, depth in kilometers).
:type picks: list of :class:`~obspy.core.event.Pick`
:param picks: Original picks used to generate the NonLinLoc location.
If provided, the output event will include the original picks and the
arrivals in the output origin will link to them correctly (with their
``pick_id`` attribute). If not provided, the output event will include
(the rather basic) pick information that can be reconstructed from the
NonLinLoc hypocenter-phase file.
:rtype: :class:`~obspy.core.event.Catalog`
"""
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()
lines = data.splitlines()
# remember picks originally used in location, if provided
original_picks = picks
if original_picks is None:
original_picks = []
# determine indices of block start/end of the NLLOC output file
indices_hyp = [None, None]
indices_phases = [None, None]
for i, line in enumerate(lines):
if line.startswith("NLLOC "):
indices_hyp[0] = i
elif line.startswith("END_NLLOC"):
indices_hyp[1] = i
elif line.startswith("PHASE "):
indices_phases[0] = i
elif line.startswith("END_PHASE"):
indices_phases[1] = i
if any([i is None for i in indices_hyp]):
msg = ("NLLOC HYP file seems corrupt,"
" could not detect 'NLLOC' and 'END_NLLOC' lines.")
raise RuntimeError(msg)
# strip any other lines around NLLOC block
lines = lines[indices_hyp[0]:indices_hyp[1]]
# 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])
line = lines["SIGNATURE"]
line = line.rstrip().split('"')[1]
signature, version, date, time = line.rsplit(" ", 3)
creation_time = UTCDateTime().strptime(date + time, str("%d%b%Y%Hh%Mm%S"))
# maximum likelihood origin location info line
line = lines["HYPOCENTER"]
x, y, z = map(float, line.split()[1:7:2])
if coordinate_converter:
x, y, z = coordinate_converter(x, y, z)
# origin time info line
line = lines["GEOGRAPHIC"]
year, month, day, hour, minute = map(int, line.split()[1:6])
seconds = float(line.split()[6])
time = UTCDateTime(year, month, day, hour, minute, seconds)
# 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"]
hor_unc, min_hor_unc, max_hor_unc, hor_unc_azim = \
map(float, line.split()[1:9:2])
# assign origin info
event = Event()
cat = Catalog(events=[event])
o = Origin()
event.origins = [o]
o.origin_uncertainty = OriginUncertainty()
o.quality = OriginQuality()
ou = o.origin_uncertainty
oq = o.quality
o.comments.append(Comment(text=stats_info_string))
cat.creation_info.creation_time = UTCDateTime()
cat.creation_info.version = "ObsPy %s" % __version__
event.creation_info = CreationInfo(creation_time=creation_time,
version=version)
event.creation_info.version = version
o.creation_info = CreationInfo(creation_time=creation_time,
version=version)
# 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()
wid = WaveformStreamID(station_code=station)
date, hourmin, sec = map(str, line[6:9])
t = UTCDateTime().strptime(date + hourmin, "%Y%m%d%H%M") + 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
return cat
def _parseRecordDp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._intZero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + "." + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == "FX":
orig_time_stderr = "Fixed"
else:
orig_time_stderr = self._floatWithFormat(orig_time_stderr, "2.1", scale)
centroid_latitude = self._floatWithFormat(line[17:21], "4.2")
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinateSign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == "FX":
lat_stderr = "Fixed"
else:
lat_stderr = self._floatWithFormat(lat_stderr, "3.2", scale)
centroid_longitude = self._floatWithFormat(line[25:30], "5.2")
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinateSign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == "FX":
lon_stderr = "Fixed"
else:
lon_stderr = self._floatWithFormat(lon_stderr, "3.2", scale)
centroid_depth = self._floatWithFormat(line[34:38], "4.1")
depth_stderr = line[38:40]
if depth_stderr == "FX" or depth_stderr == "BD":
depth_stderr = "Fixed"
else:
depth_stderr = self._floatWithFormat(depth_stderr, "2.1", scale)
station_number = self._intZero(line[40:43])
component_number = self._intZero(line[43:46])
station_number2 = self._intZero(line[46:48])
component_number2 = self._intZero(line[48:51])
# unused: half_duration = self._floatWithFormat(line[51:54], '3.1')
moment = self._floatWithFormat(line[54:56], "2.1")
moment_stderr = self._floatWithFormat(line[56:58], "2.1")
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split("/")[-1]
# Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != ".":
origin = Origin()
res_id = "/".join(
(res_id_prefix, "origin", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime("%Y%m%d")
origin.time = UTCDateTime(date + centroid_origin_time)
# Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._storeUncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == "Fixed" and lon_stderr == "Fixed":
origin.epicenter_fixed = True
else:
self._storeUncertainty(origin.latitude_errors, self._latErrToDeg(lat_stderr))
self._storeUncertainty(origin.longitude_errors, self._lonErrToDeg(lon_stderr, origin.latitude))
if depth_stderr == "Fixed":
origin.depth_type = "operator assigned"
else:
origin.depth_type = "from location"
self._storeUncertainty(origin.depth_errors, depth_stderr, scale=1000)
quality = OriginQuality()
quality.used_station_count = station_number + station_number2
quality.used_phase_count = component_number + component_number2
origin.quality = quality
origin.type = "centroid"
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = "/".join(
(res_id_prefix, "focalmechanism", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info = CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
# this is required for QuakeML validation:
res_id = "/".join((res_id_prefix, "no-origin"))
moment_tensor.derived_origin_id = ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = "/".join(
(res_id_prefix, "momenttensor", evid, source_contributor.lower(), "mw" + computation_type.lower())
)
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._storeUncertainty(moment_tensor.scalar_moment_errors, moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == "C":
res_id = "/".join((res_id_prefix, "methodID=CMT"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# CMT algorithm uses long-period body waves,
# very-long-period surface waves and
# intermediate period surface waves (since 2004
# for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = "combined"
if computation_type == "M":
res_id = "/".join((res_id_prefix, "methodID=moment_tensor"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used by
# "moment tensor" algorithm.
data_used.wave_type = "unknown"
elif computation_type == "B":
res_id = "/".join((res_id_prefix, "methodID=broadband_data"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: is 'combined' correct here?
data_used.wave_type = "combined"
elif computation_type == "F":
res_id = "/".join((res_id_prefix, "methodID=P-wave_first_motion"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = "P waves"
elif computation_type == "S":
res_id = "/".join((res_id_prefix, "methodID=scalar_moment"))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used
# for scalar moment determination.
data_used.wave_type = "unknown"
moment_tensor.data_used = data_used
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def _parse_first_line_origin(self, line, event, magnitudes):
"""
Parse the first line of origin data.
:type line: str
:param line: Line to parse.
:type event: :class:`~obspy.core.event.event.Event`
:param event: Event of the origin.
:type magnitudes: list of
:class:`~obspy.core.event.magnitude.Magnitude`
:param magnitudes: Store magnitudes in a list to keep
their positions.
:rtype: :class:`~obspy.core.event.origin.Origin`,
:class:`~obspy.core.event.resourceid.ResourceIdentifier`
:returns: Parsed origin or None, resource identifier of the
origin.
"""
magnitude_types = []
magnitude_values = []
magnitude_station_counts = []
fields = self.fields['line_1']
time_origin = line[fields['time']].strip()
time_fixed_flag = line[fields['time_fixf']].strip()
latitude = line[fields['lat']].strip()
longitude = line[fields['lon']].strip()
epicenter_fixed_flag = line[fields['epicenter_fixf']].strip()
depth = line[fields['depth']].strip()
depth_fixed_flag = line[fields['depth_fixf']].strip()
phase_count = line[fields['n_def']].strip()
station_count = line[fields['n_sta']].strip()
azimuthal_gap = line[fields['gap']].strip()
magnitude_types.append(line[fields['mag_type_1']].strip())
magnitude_values.append(line[fields['mag_1']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_1']].strip())
magnitude_types.append(line[fields['mag_type_2']].strip())
magnitude_values.append(line[fields['mag_2']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_2']].strip())
magnitude_types.append(line[fields['mag_type_3']].strip())
magnitude_values.append(line[fields['mag_3']].strip())
magnitude_station_counts.append(line[fields['mag_n_sta_3']].strip())
author = line[fields['author']].strip()
origin_id = line[fields['id']].strip()
origin = Origin()
origin.quality = OriginQuality()
try:
origin.time = UTCDateTime(time_origin.replace('/', '-'))
origin.latitude = float(latitude)
origin.longitude = float(longitude)
except (TypeError, ValueError):
self._warn('Missing origin data, skipping event')
return None, None
origin.time_fixed = time_fixed_flag.lower() == 'f'
origin.epicenter_fixed = epicenter_fixed_flag.lower() == 'f'
try:
# Convert value from km to m
origin.depth = float(depth) * 1000
except ValueError:
pass
try:
origin.depth_type = DEPTH_TYPES[depth_fixed_flag]
except KeyError:
origin.depth_type = OriginDepthType('from location')
try:
origin.quality.used_phase_count = int(phase_count)
origin.quality.associated_phase_count = int(phase_count)
except ValueError:
pass
try:
origin.quality.used_station_count = int(station_count)
origin.quality.associated_station_count = int(station_count)
except ValueError:
pass
try:
origin.quality.azimuthal_gap = float(azimuthal_gap)
except ValueError:
pass
self.author = author
origin.creation_info = self._get_creation_info()
public_id = "origin/%s" % origin_id
origin_res_id = self._get_res_id(public_id)
for i in range(3):
try:
magnitude = Magnitude()
magnitude.creation_info = self._get_creation_info()
magnitude.magnitude_type = magnitude_types[i]
magnitude.mag = float(magnitude_values[i])
magnitude.station_count = int(magnitude_station_counts[i])
magnitude.origin_id = origin_res_id
magnitudes.append(magnitude)
event.magnitudes.append(magnitude)
except ValueError:
# Magnitude can be empty but we need to keep the
# position between mag1, mag2 or mag3.
magnitudes.append(None)
return origin, origin_res_id
def _parse_record_dp(self, line, event):
"""
Parses the 'source parameter data - primary' record Dp
"""
source_contributor = line[2:6].strip()
computation_type = line[6]
exponent = self._int_zero(line[7])
scale = math.pow(10, exponent)
centroid_origin_time = line[8:14] + '.' + line[14]
orig_time_stderr = line[15:17]
if orig_time_stderr == 'FX':
orig_time_stderr = 'Fixed'
else:
orig_time_stderr = \
self._float_with_format(orig_time_stderr, '2.1', scale)
centroid_latitude = self._float_with_format(line[17:21], '4.2')
lat_type = line[21]
if centroid_latitude is not None:
centroid_latitude *= self._coordinate_sign(lat_type)
lat_stderr = line[22:25]
if lat_stderr == 'FX':
lat_stderr = 'Fixed'
else:
lat_stderr = self._float_with_format(lat_stderr, '3.2', scale)
centroid_longitude = self._float_with_format(line[25:30], '5.2')
lon_type = line[30]
if centroid_longitude is not None:
centroid_longitude *= self._coordinate_sign(lon_type)
lon_stderr = line[31:34]
if lon_stderr == 'FX':
lon_stderr = 'Fixed'
else:
lon_stderr = self._float_with_format(lon_stderr, '3.2', scale)
centroid_depth = self._float_with_format(line[34:38], '4.1')
depth_stderr = line[38:40]
if depth_stderr == 'FX' or depth_stderr == 'BD':
depth_stderr = 'Fixed'
else:
depth_stderr = self._float_with_format(depth_stderr, '2.1', scale)
station_number = self._int_zero(line[40:43])
component_number = self._int_zero(line[43:46])
station_number2 = self._int_zero(line[46:48])
component_number2 = self._int_zero(line[48:51])
# unused: half_duration = self._float_with_format(line[51:54], '3.1')
moment = self._float_with_format(line[54:56], '2.1')
moment_stderr = self._float_with_format(line[56:58], '2.1')
moment_exponent = self._int(line[58:60])
if (moment is not None) and (moment_exponent is not None):
moment *= math.pow(10, moment_exponent)
if (moment_stderr is not None) and (moment_exponent is not None):
moment_stderr *= math.pow(10, moment_exponent)
evid = event.resource_id.id.split('/')[-1]
# Create a new origin only if centroid time is defined:
origin = None
if centroid_origin_time.strip() != '.':
origin = Origin()
res_id = '/'.join((res_id_prefix, 'origin',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
origin.resource_id = ResourceIdentifier(id=res_id)
origin.creation_info = \
CreationInfo(agency_id=source_contributor)
date = event.origins[0].time.strftime('%Y%m%d')
origin.time = UTCDateTime(date + centroid_origin_time)
# Check if centroid time is on the next day:
if origin.time < event.origins[0].time:
origin.time += timedelta(days=1)
self._store_uncertainty(origin.time_errors, orig_time_stderr)
origin.latitude = centroid_latitude
origin.longitude = centroid_longitude
origin.depth = centroid_depth * 1000
if lat_stderr == 'Fixed' and lon_stderr == 'Fixed':
origin.epicenter_fixed = True
else:
self._store_uncertainty(origin.latitude_errors,
self._lat_err_to_deg(lat_stderr))
self._store_uncertainty(origin.longitude_errors,
self._lon_err_to_deg(lon_stderr,
origin.latitude))
if depth_stderr == 'Fixed':
origin.depth_type = 'operator assigned'
else:
origin.depth_type = 'from location'
self._store_uncertainty(origin.depth_errors,
depth_stderr, scale=1000)
quality = OriginQuality()
quality.used_station_count = \
station_number + station_number2
quality.used_phase_count = \
component_number + component_number2
origin.quality = quality
origin.origin_type = 'centroid'
event.origins.append(origin)
focal_mechanism = FocalMechanism()
res_id = '/'.join((res_id_prefix, 'focalmechanism',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
focal_mechanism.resource_id = ResourceIdentifier(id=res_id)
focal_mechanism.creation_info = \
CreationInfo(agency_id=source_contributor)
moment_tensor = MomentTensor()
if origin is not None:
moment_tensor.derived_origin_id = origin.resource_id
else:
# this is required for QuakeML validation:
res_id = '/'.join((res_id_prefix, 'no-origin'))
moment_tensor.derived_origin_id = \
ResourceIdentifier(id=res_id)
for mag in event.magnitudes:
if mag.creation_info.agency_id == source_contributor:
moment_tensor.moment_magnitude_id = mag.resource_id
res_id = '/'.join((res_id_prefix, 'momenttensor',
evid, source_contributor.lower(),
'mw' + computation_type.lower()))
moment_tensor.resource_id = ResourceIdentifier(id=res_id)
moment_tensor.scalar_moment = moment
self._store_uncertainty(moment_tensor.scalar_moment_errors,
moment_stderr)
data_used = DataUsed()
data_used.station_count = station_number + station_number2
data_used.component_count = component_number + component_number2
if computation_type == 'C':
res_id = '/'.join((res_id_prefix, 'methodID=CMT'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# CMT algorithm uses long-period body waves,
# very-long-period surface waves and
# intermediate period surface waves (since 2004
# for shallow and intermediate-depth earthquakes
# --Ekstrom et al., 2012)
data_used.wave_type = 'combined'
if computation_type == 'M':
res_id = '/'.join((res_id_prefix, 'methodID=moment_tensor'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used by
# "moment tensor" algorithm.
data_used.wave_type = 'unknown'
elif computation_type == 'B':
res_id = '/'.join((res_id_prefix, 'methodID=broadband_data'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: is 'combined' correct here?
data_used.wave_type = 'combined'
elif computation_type == 'F':
res_id = '/'.join((res_id_prefix, 'methodID=P-wave_first_motion'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
data_used.wave_type = 'P waves'
elif computation_type == 'S':
res_id = '/'.join((res_id_prefix, 'methodID=scalar_moment'))
focal_mechanism.method_id = ResourceIdentifier(id=res_id)
# FIXME: not sure which kind of data is used
# for scalar moment determination.
data_used.wave_type = 'unknown'
moment_tensor.data_used = [data_used]
focal_mechanism.moment_tensor = moment_tensor
event.focal_mechanisms.append(focal_mechanism)
return focal_mechanism
def outputOBSPY(hp, event=None, only_fm_picks=False):
"""
Make an Event which includes the current focal mechanism information from HASH
Use the 'only_fm_picks' flag to only include the picks HASH used for the FocalMechanism.
This flag will replace the 'picks' and 'arrivals' lists of existing events with new ones.
Inputs
-------
hp : hashpy.HashPype instance
event : obspy.core.event.Event
only_fm_picks : bool of whether to overwrite the picks/arrivals lists
Returns
-------
obspy.core.event.Event
Event will be new if no event was input, FocalMech added to existing event
"""
# Returns new (or updates existing) Event with HASH solution
n = hp.npol
if event is None:
event = Event(focal_mechanisms=[], picks=[], origins=[])
origin = Origin(arrivals=[])
origin.time = UTCDateTime(hp.tstamp)
origin.latitude = hp.qlat
origin.longitude = hp.qlon
origin.depth = hp.qdep
origin.creation_info = CreationInfo(version=hp.icusp)
origin.resource_id = ResourceIdentifier('smi:hash/Origin/{0}'.format(hp.icusp))
for _i in range(n):
p = Pick()
p.creation_info = CreationInfo(version=hp.arid[_i])
p.resource_id = ResourceIdentifier('smi:hash/Pick/{0}'.format(p.creation_info.version))
p.waveform_id = WaveformStreamID(network_code=hp.snet[_i], station_code=hp.sname[_i], channel_code=hp.scomp[_i])
if hp.p_pol[_i] > 0:
p.polarity = 'positive'
else:
p.polarity = 'negative'
a = Arrival()
a.creation_info = CreationInfo(version=hp.arid[_i])
a.resource_id = ResourceIdentifier('smi:hash/Arrival/{0}'.format(p.creation_info.version))
a.azimuth = hp.p_azi_mc[_i,0]
a.takeoff_angle = 180. - hp.p_the_mc[_i,0]
a.pick_id = p.resource_id
origin.arrivals.append(a)
event.picks.append(p)
event.origins.append(origin)
event.preferred_origin_id = str(origin.resource_id)
else: # just update the changes
origin = event.preferred_origin()
picks = []
arrivals = []
for _i in range(n):
ind = hp.p_index[_i]
a = origin.arrivals[ind]
p = a.pick_id.getReferredObject()
a.takeoff_angle = hp.p_the_mc[_i,0]
picks.append(p)
arrivals.append(a)
if only_fm_picks:
origin.arrivals = arrivals
event.picks = picks
# Use me double couple calculator and populate planes/axes etc
x = hp._best_quality_index
# Put all the mechanisms into the 'focal_mechanisms' list, mark "best" as preferred
for s in range(hp.nmult):
dc = DoubleCouple([hp.str_avg[s], hp.dip_avg[s], hp.rak_avg[s]])
ax = dc.axis
focal_mech = FocalMechanism()
focal_mech.creation_info = CreationInfo(creation_time=UTCDateTime(), author=hp.author)
focal_mech.triggering_origin_id = origin.resource_id
focal_mech.resource_id = ResourceIdentifier('smi:hash/FocalMechanism/{0}/{1}'.format(hp.icusp, s+1))
focal_mech.method_id = ResourceIdentifier('HASH')
focal_mech.nodal_planes = NodalPlanes()
focal_mech.nodal_planes.nodal_plane_1 = NodalPlane(*dc.plane1)
focal_mech.nodal_planes.nodal_plane_2 = NodalPlane(*dc.plane2)
focal_mech.principal_axes = PrincipalAxes()
focal_mech.principal_axes.t_axis = Axis(azimuth=ax['T']['azimuth'], plunge=ax['T']['dip'])
focal_mech.principal_axes.p_axis = Axis(azimuth=ax['P']['azimuth'], plunge=ax['P']['dip'])
focal_mech.station_polarity_count = n
focal_mech.azimuthal_gap = hp.magap
focal_mech.misfit = hp.mfrac[s]
focal_mech.station_distribution_ratio = hp.stdr[s]
focal_mech.comments.append(
Comment(hp.qual[s], resource_id=ResourceIdentifier(str(focal_mech.resource_id) + '/comment/quality'))
)
#----------------------------------------
event.focal_mechanisms.append(focal_mech)
if s == x:
event.preferred_focal_mechanism_id = str(focal_mech.resource_id)
return event
def build(self):
"""
Build an obspy moment tensor focal mech event
This makes the tensor output into an Event containing:
1) a FocalMechanism with a MomentTensor, NodalPlanes, and PrincipalAxes
2) a Magnitude of the Mw from the Tensor
Which is what we want for outputting QuakeML using
the (slightly modified) obspy code.
Input
-----
filehandle => open file OR str from filehandle.read()
Output
------
event => instance of Event() class as described above
"""
p = self.parser
event = Event(event_type='earthquake')
origin = Origin()
focal_mech = FocalMechanism()
nodal_planes = NodalPlanes()
moment_tensor = MomentTensor()
principal_ax = PrincipalAxes()
magnitude = Magnitude()
data_used = DataUsed()
creation_info = CreationInfo(agency_id='NN')
ev_mode = 'automatic'
ev_stat = 'preliminary'
evid = None
orid = None
# Parse the entire file line by line.
for n,l in enumerate(p.line):
if 'REVIEWED BY NSL STAFF' in l:
ev_mode = 'manual'
ev_stat = 'reviewed'
if 'Event ID' in l:
evid = p._id(n)
if 'Origin ID' in l:
orid = p._id(n)
if 'Ichinose' in l:
moment_tensor.category = 'regional'
if re.match(r'^\d{4}\/\d{2}\/\d{2}', l):
ev = p._event_info(n)
if 'Depth' in l:
derived_depth = p._depth(n)
if 'Mw' in l:
magnitude.mag = p._mw(n)
magnitude.magnitude_type = 'Mw'
if 'Mo' in l and 'dyne' in l:
moment_tensor.scalar_moment = p._mo(n)
if 'Percent Double Couple' in l:
moment_tensor.double_couple = p._percent(n)
if 'Percent CLVD' in l:
moment_tensor.clvd = p._percent(n)
if 'Epsilon' in l:
moment_tensor.variance = p._epsilon(n)
if 'Percent Variance Reduction' in l:
moment_tensor.variance_reduction = p._percent(n)
if 'Major Double Couple' in l and 'strike' in p.line[n+1]:
np = p._double_couple(n)
nodal_planes.nodal_plane_1 = NodalPlane(*np[0])
nodal_planes.nodal_plane_2 = NodalPlane(*np[1])
nodal_planes.preferred_plane = 1
if 'Spherical Coordinates' in l:
mt = p._mt_sphere(n)
moment_tensor.tensor = Tensor(
m_rr = mt['Mrr'],
m_tt = mt['Mtt'],
m_pp = mt['Mff'],
m_rt = mt['Mrt'],
m_rp = mt['Mrf'],
m_tp = mt['Mtf'],
)
if 'Eigenvalues and eigenvectors of the Major Double Couple' in l:
ax = p._vectors(n)
principal_ax.t_axis = Axis(ax['T']['trend'], ax['T']['plunge'], ax['T']['ev'])
principal_ax.p_axis = Axis(ax['P']['trend'], ax['P']['plunge'], ax['P']['ev'])
principal_ax.n_axis = Axis(ax['N']['trend'], ax['N']['plunge'], ax['N']['ev'])
if 'Number of Stations' in l:
data_used.station_count = p._number_of_stations(n)
if 'Maximum' in l and 'Gap' in l:
focal_mech.azimuthal_gap = p._gap(n)
if re.match(r'^Date', l):
creation_info.creation_time = p._creation_time(n)
# Creation Time
creation_info.version = orid
# Fill in magnitude values
magnitude.evaluation_mode = ev_mode
magnitude.evaluation_status = ev_stat
magnitude.creation_info = creation_info.copy()
magnitude.resource_id = self._rid(magnitude)
# Stub origin
origin.time = ev.get('time')
origin.latitude = ev.get('lat')
origin.longitude = ev.get('lon')
origin.depth = derived_depth * 1000.
origin.depth_type = "from moment tensor inversion"
origin.creation_info = creation_info.copy()
# Unique from true origin ID
_oid = self._rid(origin)
origin.resource_id = ResourceIdentifier(str(_oid) + '/mt')
del _oid
# Make an id for the MT that references this origin
ogid = str(origin.resource_id)
doid = ResourceIdentifier(ogid, referred_object=origin)
# Make an id for the moment tensor mag which references this mag
mrid = str(magnitude.resource_id)
mmid = ResourceIdentifier(mrid, referred_object=magnitude)
# MT todo: could check/use URL for RID if parsing the php file
moment_tensor.evaluation_mode = ev_mode
moment_tensor.evaluation_status = ev_stat
moment_tensor.data_used = data_used
moment_tensor.moment_magnitude_id = mmid
moment_tensor.derived_origin_id = doid
moment_tensor.creation_info = creation_info.copy()
moment_tensor.resource_id = self._rid(moment_tensor)
# Fill in focal_mech values
focal_mech.nodal_planes = nodal_planes
focal_mech.moment_tensor = moment_tensor
focal_mech.principal_axes = principal_ax
focal_mech.creation_info = creation_info.copy()
focal_mech.resource_id = self._rid(focal_mech)
# add mech and new magnitude to event
event.focal_mechanisms = [focal_mech]
event.magnitudes = [magnitude]
event.origins = [origin]
event.creation_info = creation_info.copy()
# If an MT was done, that's the preferred mag/mech
event.preferred_magnitude_id = str(magnitude.resource_id)
event.preferred_focal_mechanism_id = str(focal_mech.resource_id)
if evid:
event.creation_info.version = evid
event.resource_id = self._rid(event)
self.event = event
def _map_join2origin(self, db):
"""
Return an Origin instance from an dict of CSS key/values
Inputs
======
db : dict of key/values of CSS fields related to the origin (see Join)
Returns
=======
obspy.core.event.Origin
Notes
=====
Any object that supports the dict 'get' method can be passed as
input, e.g. OrderedDict, custom classes, etc.
Join
----
origin <- origerr (outer)
"""
#-- Basic location ------------------------------------------
origin = Origin()
origin.latitude = db.get('lat')
origin.longitude = db.get('lon')
origin.depth = _km2m(db.get('depth'))
origin.time = _utc(db.get('time'))
origin.extra = {}
#-- Quality -------------------------------------------------
quality = OriginQuality(
associated_phase_count = db.get('nass'),
used_phase_count = db.get('ndef'),
standard_error = db.get('sdobs'),
)
origin.quality = quality
#-- Solution Uncertainties ----------------------------------
# in CSS the ellipse is projected onto the horizontal plane
# using the covariance matrix
uncertainty = OriginUncertainty()
a = _km2m(db.get('smajax'))
b = _km2m(db.get('sminax'))
s = db.get('strike')
dep_u = _km2m(db.get('sdepth'))
time_u = db.get('stime')
uncertainty.max_horizontal_uncertainty = a
uncertainty.min_horizontal_uncertainty = b
uncertainty.azimuth_max_horizontal_uncertainty = s
uncertainty.horizontal_uncertainty = a
uncertainty.preferred_description = "horizontal uncertainty"
if db.get('conf') is not None:
uncertainty.confidence_level = db.get('conf') * 100.
if uncertainty.horizontal_uncertainty is not None:
origin.origin_uncertainty = uncertainty
#-- Parameter Uncertainties ---------------------------------
if all([a, b, s]):
n, e = _get_NE_on_ellipse(a, b, s)
lat_u = _m2deg_lat(n)
lon_u = _m2deg_lon(e, lat=origin.latitude)
origin.latitude_errors = {'uncertainty': lat_u}
origin.longitude_errors = {'uncertainty': lon_u}
if dep_u:
origin.depth_errors = {'uncertainty': dep_u}
if time_u:
origin.time_errors = {'uncertainty': time_u}
#-- Analyst-determined Status -------------------------------
posted_author = _str(db.get('auth'))
mode, status = self.get_event_status(posted_author)
origin.evaluation_mode = mode
origin.evaluation_status = status
# Save etype per origin due to schema differences...
css_etype = _str(db.get('etype'))
# Compatible with future patch rename "_namespace" -> "namespace"
origin.extra['etype'] = {
'value': css_etype,
'namespace': CSS_NAMESPACE
}
origin.creation_info = CreationInfo(
creation_time = _utc(db.get('lddate')),
agency_id = self.agency,
version = db.get('orid'),
author = posted_author,
)
origin.resource_id = self._rid(origin)
return origin
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 _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
