Python DistancesContext.rrup方法代碼示例

# 需要導入模塊: from openquake.hazardlib.gsim.base import DistancesContext [as 別名]
# 或者: from openquake.hazardlib.gsim.base.DistancesContext import rrup [as 別名]
    def test_mag_greater_8pt5(self):
        gmpe = SadighEtAl1997()

        sctx = SitesContext()
        rctx = RuptureContext()
        dctx = DistancesContext()

        rctx.rake =  0.0
        dctx.rrup = numpy.array([0., 1.])
        sctx.vs30 = numpy.array([800., 800.])

        rctx.mag = 9.0
        mean_rock_9, _ = gmpe.get_mean_and_stddevs(
            sctx, rctx, dctx, PGA(), [StdDev.TOTAL]
        )
        rctx.mag = 8.5
        mean_rock_8pt5, _ = gmpe.get_mean_and_stddevs(
            sctx, rctx, dctx, PGA(), [StdDev.TOTAL]
        )
        numpy.testing.assert_allclose(mean_rock_9, mean_rock_8pt5)

        sctx.vs30 = numpy.array([300., 300.])
        rctx.mag = 9.0
        mean_soil_9, _ = gmpe.get_mean_and_stddevs(
            sctx, rctx, dctx, PGA(), [StdDev.TOTAL]
        )
        rctx.mag = 8.5
        mean_soil_8pt5, _ = gmpe.get_mean_and_stddevs(
            sctx, rctx, dctx, PGA(), [StdDev.TOTAL]
        )
        numpy.testing.assert_allclose(mean_soil_9, mean_soil_8pt5)

# 需要導入模塊: from openquake.hazardlib.gsim.base import DistancesContext [as 別名]
# 或者: from openquake.hazardlib.gsim.base.DistancesContext import rrup [as 別名]
IMT = imt.PGA()
rctx = RuptureContext()
dctx = DistancesContext()
sctx = SitesContext()
sctx_rock = SitesContext()

rctx.rake = 0.0
rctx.dip = 90.0
rctx.ztor = 7.13
rctx.mag = 3.0
#rctx.mag = np.linspace(0.1,5.)
rctx.width = 10.0
rctx.hypo_depth = 8.0

#dctx.rrup = np.logspace(1,np.log10(200),100)
dctx.rrup = np.logspace(np.log10(10),np.log10(10.0),1)


# Assuming average ztor, get rjb:
dctx.rjb = np.sqrt(dctx.rrup**2 - rctx.ztor**2)
dctx.rhypo = dctx.rrup
dctx.rx = dctx.rjb
dctx.ry0 = dctx.rx

sctx.vs30 = np.ones_like(dctx.rrup) * 760.0
sctx.vs30measured = np.full_like(dctx.rrup, False, dtype='bool')
sctx.z1pt0 = np.ones_like(dctx.rrup) * 0.05

lmean_ask14, sd_ask14 = ASK14.get_mean_and_stddevs(
    sctx, rctx, dctx, IMT, [const.StdDev.TOTAL])

# 需要導入模塊: from openquake.hazardlib.gsim.base import DistancesContext [as 別名]
# 或者: from openquake.hazardlib.gsim.base.DistancesContext import rrup [as 別名]
def signal_end(st, event_time, event_lon, event_lat, event_mag,
               method=None, vmin=None, floor=None,
               model=None, epsilon=2.0):
    """
    Estimate end of signal by using a model of the 5-95% significant
    duration, and adding this value to the "signal_split" time. This probably
    only works well when the split is estimated with a p-wave picker since
    the velocity method often ends up with split times that are well before
    signal actually starts.

    Args:
        st (StationStream):
            Stream of data.
        event_time (UTCDateTime):
            Event origin time.
        event_mag (float):
            Event magnitude.
        event_lon (float):
            Event longitude.
        event_lat (float):
            Event latitude.
        method (str):
            Method for estimating signal end time. Either 'velocity'
            or 'model'.
        vmin (float):
            Velocity (km/s) for estimating end of signal. Only used if
            method="velocity".
        floor (float):
            Minimum duration (sec) applied along with vmin.
        model (str):
            Short name of duration model to use. Must be defined in the
            gmprocess/data/modules.yml file.
        epsilon (float):
            Number of standard deviations; if epsilon is 1.0, then the signal
            window duration is the mean Ds + 1 standard deviation. Only used
            for method="model".

    Returns:
        trace with stats dict updated to include a
        stats['processing_parameters']['signal_end'] dictionary.

    """
    # Load openquake stuff if method="model"
    if method == "model":
        mod_file = pkg_resources.resource_filename(
            'gmprocess', os.path.join('data', 'modules.yml'))
        with open(mod_file, 'r') as f:
            mods = yaml.load(f)

        # Import module
        cname, mpath = mods['modules'][model]
        dmodel = getattr(import_module(mpath), cname)()

        # Set some "conservative" inputs (in that they will tend to give
        # larger durations).
        sctx = SitesContext()
        sctx.vs30 = np.array([180.0])
        sctx.z1pt0 = np.array([0.51])
        rctx = RuptureContext()
        rctx.mag = event_mag
        rctx.rake = -90.0
        dur_imt = imt.from_string('RSD595')
        stddev_types = [const.StdDev.INTRA_EVENT]

    for tr in st:
        if not tr.hasParameter('signal_split'):
            continue
        if method == "velocity":
            if vmin is None:
                raise ValueError('Must specify vmin if method is "velocity".')
            if floor is None:
                raise ValueError('Must specify floor if method is "velocity".')
            epi_dist = gps2dist_azimuth(
                lat1=event_lat,
                lon1=event_lon,
                lat2=tr.stats['coordinates']['latitude'],
                lon2=tr.stats['coordinates']['longitude'])[0] / 1000.0
            end_time = event_time + max(floor, epi_dist / vmin)
        elif method == "model":
            if model is None:
                raise ValueError('Must specify model if method is "model".')
            epi_dist = gps2dist_azimuth(
                lat1=event_lat,
                lon1=event_lon,
                lat2=tr.stats['coordinates']['latitude'],
                lon2=tr.stats['coordinates']['longitude'])[0] / 1000.0
            dctx = DistancesContext()
            # Repi >= Rrup, so substitution here should be conservative
            # (leading to larger durations).
            dctx.rrup = np.array([epi_dist])
            lnmu, lnstd = dmodel.get_mean_and_stddevs(
                sctx, rctx, dctx, dur_imt, stddev_types)
            duration = np.exp(lnmu + epsilon * lnstd[0])
            # Get split time
            split_time = tr.getParameter('signal_split')['split_time']
            end_time = split_time + float(duration)
        else:
            raise ValueError('method must be either "velocity" or "model".')
        # Update trace params
        end_params = {
#.........這裏部分代碼省略.........