Python Event.origins方法代码示例

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]
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
#.........这里部分代码省略.........

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]

#.........这里部分代码省略.........
            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,

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]
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

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]

#.........这里部分代码省略.........
    # 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:

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]

#.........这里部分代码省略.........
                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

# 需要导入模块: from obspy.core.event import Event [as 别名]
# 或者: from obspy.core.event.Event import origins [as 别名]
    def get_results(self):
        cids = []
        clusters = []
        results_file = "{}/{}".format(self.hypoDD_control.control_directory,
                              self.hypoDD_control.relocated_hypocenters_output
                              )
        residuals_file = "{}/{}".format(self.hypoDD_control.control_directory,
                                        self.hypoDD_control.data_residual_output
                                        )
        with open(results_file, "r") as f:
            for line in f:
                num = line.split()
                evid = num[0]
                lat = float(num[1])
                lon = float(num[2])
                dep = 1000 * float(num[3])  # km to m
                errx = num[7]
                erry = num[8]
                errz = num[9]
                yr = int(num[10])
                mo = int(num[11])
                dy = int(num[12])
                hr = int(num[13])
                mi = int(num[14])
                sc = float(num[15])
                mag = num[16]
                nccp = num[17]
                nccs = num[18]
                nctp = num[19]
                ncts = num[20]
                rcc = num[21]
                rct = num[22]
                cid = num[23]
                if cid not in cids:
                    cids.append(cid)
                    clusters.append(Cluster())
                    clusters[-1].hypoDD_id=cid
                    clusters[-1].successful_relocation=True
                    clusters[-1].catalog=Catalog()
                    clusters[-1].event_ids=[]
                origin=Origin()
                isec = int ( math.floor( sc ))
                micsec = int ( ( sc - isec) * 1000000 )
                origin.time = UTCDateTime(yr, mo, dy, hr, mi, isec, micsec)
                origin.longitude = lon
                origin.latitude = lat
                origin.depth = dep
                origin.method_id = "hypoDD"
                # TODO (@ogalanis): Add time/location errors (when
                # appropriate. Add quality and origin_uncertainty. Add arrivals.
                event=Event()
                event.creation_info=CreationInfo()
                event.creation_info.author = __package__
                event.creation_info.version = info.__version__
                event.origins=[origin]
                event.magnitude=Magnitude()
                event.magnitude.mag=mag
                idx=cids.index(cid)
                clusters[idx].catalog.events.append(event)
                clusters[idx].event_ids.append(evid)

        if self.hypoDD_control.cid != 0 :
            my_list = []
            clusters[0].connectedness = Connectedness()
            with open(residuals_file, "r") as f:
                for line in f:
                    num = line.split()
                    evid_1 = num[2]
                    evid_2 = num[3]
                    obs_type = num[4]
                    if obs_type == "1":
                        my_list = clusters[0].connectedness.cross_corr_P
                    elif obs_type == "2":
                        my_list = clusters[0].connectedness.cross_corr_S
                    elif obs_type == "3":
                        my_list = clusters[0].connectedness.catalog_P
                    elif obs_type == "4":
                        my_list = clusters[0].connectedness.catalog_S
                    else:
                        continue
                    in_list = [x for x in my_list if (( x[0] == evid_1 and
                                                        x[1] == evid_2
                                                        ) or
                                                      ( x[0] == evid_2 and
                                                        x[1] == evid_1
                                                        ))]
                    if in_list:
                        for x in my_list:
                            if (( x[0] == evid_1 and
                                  x[1] == evid_2
                                  ) or
                                ( x[0] == evid_2 and
                                  x[1] == evid_1
                                  )):
                                x[2] += 1
                    else:
                        my_list.append([evid_1,evid_2,1])

        return clusters