Source code for openquake.hazardlib.gsim.boore_2014

# The Hazard Library
# Copyright (C) 2012-2014, GEM Foundation
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
"""
Module exports :class:`BooreEtAl2014`,
               :class:`BooreEtAl2014HighQ`,
               :class:`BooreEtAl2014LowQ`,
               :class:`BooreEtAl2014CaliforniaBasin`,
               :class:`BooreEtAl2014HighQCaliforniaBasin`,
               :class:`BooreEtAl2014LowQCaliforniaBasin`,
               :class:`BooreEtAl2014JapanBasin`,
               :class:`BooreEtAl2014HighQJapanBasin`,
               :class:`BooreEtAl2014LowQJapanBasin`,
               :class:`BooreEtAl2014NoSOF`,
               :class:`BooreEtAl2014HighQNoSOF`,
               :class:`BooreEtAl2014LowQNoSOF`,
               :class:`BooreEtAl2014CaliforniaBasinNoSOF`,
               :class:`BooreEtAl2014HighQCaliforniaBasinNoSOF`,
               :class:`BooreEtAl2014LowQCaliforniaBasinNoSOF`,
               :class:`BooreEtAlJ2014apanBasinNoSOF`,
               :class:`BooreEtAl2014HighQJapanBasinNoSOF`,
               :class:`BooreEtAl2014LowQJapanBasinNoSOF`
"""
from __future__ import division

import numpy as np

from openquake.hazardlib.gsim.base import GMPE, CoeffsTable
from openquake.hazardlib import const
from openquake.hazardlib.imt import PGA, PGV, SA


[docs]class BooreEtAl2014(GMPE): """ Implements GMPE developed by David M. Boore, Jonathan P. Stewart, Emel Seyhan and Gail Atkinson, and published as "NGA-West2 Equations for Predicting PGA, PGV, nd 5 % Damped PGA for Shallow Crustal Earthquakes (2014, Earthquake Spectra, Volume 30, No. 3, pages 1057 - 1085). """ #: Supported tectonic region type is active shallow crust DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.ACTIVE_SHALLOW_CRUST #: Supported intensity measure types are spectral acceleration, #: peak ground velocity and peak ground acceleration DEFINED_FOR_INTENSITY_MEASURE_TYPES = set([ PGA, PGV, SA ]) #: Supported intensity measure component is orientation-independent #: measure :attr:`~openquake.hazardlib.const.IMC.RotD50` DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.RotD50 #: Supported standard deviation types are inter-event, intra-event #: and total, see equation 2, pag 106. DEFINED_FOR_STANDARD_DEVIATION_TYPES = set([ const.StdDev.TOTAL, const.StdDev.INTER_EVENT, const.StdDev.INTRA_EVENT ]) #: Required site parameters is Vs30 REQUIRES_SITES_PARAMETERS = set(('vs30', )) #: Required rupture parameters are magnitude, and rake. REQUIRES_RUPTURE_PARAMETERS = set(('mag', 'rake')) #: Required distance measure is Rjb REQUIRES_DISTANCES = set(('rjb', ))
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): """ See :meth:`superclass method <.base.GroundShakingIntensityModel.get_mean_and_stddevs>` for spec of input and result values. """ # extracting dictionary of coefficients specific to required # intensity measure type. C = self.COEFFS[imt] C_PGA = self.COEFFS[PGA()] if isinstance(imt, (PGA, PGV)): imt_per = 0.0 else: imt_per = imt.period pga_rock = self._get_pga_on_rock(C_PGA, rup, dists) mean = (self._get_magnitude_scaling_term(C, rup) + self._get_path_scaling(C, dists, rup.mag) + self._get_site_scaling(C, pga_rock, sites, imt_per, dists.rjb)) stddevs = self._get_stddevs(C, rup, dists, sites, stddev_types) return mean, stddevs
def _get_pga_on_rock(self, C, rup, dists): """ Returns the median PGA on rock, which is a sum of the magnitude and distance scaling """ return np.exp(self._get_magnitude_scaling_term(C, rup) + self._get_path_scaling(C, dists, rup.mag)) def _get_magnitude_scaling_term(self, C, rup): """ Returns the magnitude scling term defined in equation (2) """ dmag = rup.mag - C["Mh"] if rup.mag <= C["Mh"]: mag_term = (C["e4"] * dmag) + (C["e5"] * (dmag ** 2.0)) else: mag_term = C["e6"] * dmag return self._get_style_of_faulting_term(C, rup) + mag_term def _get_style_of_faulting_term(self, C, rup): """ Get fault type dummy variables Fault type (Strike-slip, Normal, Thrust/reverse) is derived from rake angle. Rakes angles within 30 of horizontal are strike-slip, angles from 30 to 150 are reverse, and angles from -30 to -150 are normal. Note that the 'Unspecified' case is not considered here as rake is always given. """ if np.abs(rup.rake) <= 30.0 or (180.0 - np.abs(rup.rake)) <= 30.0: # strike-slip return C["e1"] elif rup.rake > 30.0 and rup.rake < 150.0: # reverse return C["e3"] else: # normal return C["e2"] def _get_path_scaling(self, C, dists, mag): """ Returns the path scaling term given by equation (3) """ rval = np.sqrt((dists.rjb ** 2.0) + (C["h"] ** 2.0)) scaling = (C["c1"] + C["c2"] * (mag - self.CONSTS["Mref"])) *\ np.log(rval / self.CONSTS["Rref"]) return scaling + ((C["c3"] + C["Dc3"]) * (rval - self.CONSTS["Rref"])) def _get_site_scaling(self, C, pga_rock, sites, period, rjb): """ Returns the site-scaling term (equation 5), broken down into a linear scaling, a nonlinear scaling and a basin scaling term """ flin = self._get_linear_site_term(C, sites.vs30) fnl = self._get_nonlinear_site_term(C, sites.vs30, pga_rock) fbd = self._get_basin_depth_term(C, sites, period) return flin + fnl + fbd def _get_linear_site_term(self, C, vs30): """ Returns the linear site scaling term (equation 6) """ flin = vs30 / self.CONSTS["Vref"] flin[vs30 > C["Vc"]] = C["Vc"] / self.CONSTS["Vref"] return C["c"] * np.log(flin) def _get_nonlinear_site_term(self, C, vs30, pga_rock): """ Returns the nonlinear site scaling term (equation 7) """ v_s = np.copy(vs30) v_s[vs30 > 760.] = 760. # Nonlinear controlling parameter (equation 8) f_2 = C["f4"] * (np.exp(C["f5"] * (v_s - 360.)) - np.exp(C["f5"] * 400.)) fnl = self.CONSTS["f1"] + f_2 * np.log((pga_rock + self.CONSTS["f3"]) / self.CONSTS["f3"]) return fnl def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ return np.zeros(len(sites.vs30), dtype=float) def _get_stddevs(self, C, rup, dists, sites, stddev_types): """ Returns the aleatory uncertainty terms described in equations (13) to (17) """ stddevs = [] num_sites = len(sites.vs30) tau = self._get_inter_event_tau(C, rup.mag, num_sites) phi = self._get_intra_event_phi(C, rup.mag, dists.rjb, sites.vs30, num_sites) for stddev_type in stddev_types: assert stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES if stddev_type == const.StdDev.TOTAL: stddevs.append(np.sqrt((tau ** 2.0) + (phi ** 2.0))) elif stddev_type == const.StdDev.INTRA_EVENT: stddevs.append(phi) elif stddev_type == const.StdDev.INTER_EVENT: stddevs.append(tau) return stddevs def _get_inter_event_tau(self, C, mag, num_sites): """ Returns the inter-event standard deviation (tau), which is dependent on magnitude """ base_vals = np.zeros(num_sites) if mag <= 4.5: return base_vals + C["t1"] elif mag >= 5.5: return base_vals + C["t2"] else: return base_vals + C["t1"] + (C["t2"] - C["t1"]) * (mag - 4.5) def _get_intra_event_phi(self, C, mag, rjb, vs30, num_sites): """ Returns the intra-event standard deviation (phi), dependent on magnitude, distance and vs30 """ base_vals = np.zeros(num_sites) # Magnitude Dependent phi (Equation 17) if mag <= 4.5: base_vals += C["f1"] elif mag >= 5.5: base_vals += C["f2"] else: base_vals += (C["f1"] + (C["f2"] - C["f1"]) * (mag - 4.5)) # Distance dependent phi (Equation 16) idx1 = rjb > C["R2"] base_vals[idx1] += C["DfR"] idx2 = np.logical_and(rjb > C["R1"], rjb <= C["R2"]) base_vals[idx2] += (C["DfR"] * (np.log(rjb[idx2] / C["R1"]) / np.log(C["R2"] / C["R1"]))) # Site-dependent phi (Equation 15) idx1 = vs30 <= self.CONSTS["v1"] base_vals[idx1] -= C["DfV"] idx2 = np.logical_and(vs30 >= self.CONSTS["v1"], vs30 <= self.CONSTS["v2"]) base_vals[idx2] -= ( C["DfV"] * (np.log(self.CONSTS["v2"] / vs30[idx2]) / np.log(self.CONSTS["v2"] / self.CONSTS["v1"]))) return base_vals COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT e0 e1 e2 e3 e4 e5 e6 Mh c1 c2 c3 h Dc3 c Vc f4 f5 f6 f7 R1 R2 DfR DfV f1 f2 t1 t2 pgv 5.037000 5.078000 4.849000 5.033000 1.073000 -0.153600 0.225200 6.200000 -1.243000 0.148900 -0.003440 5.300000 0.000000 -0.840000 1300.000000 -0.100000 -0.008440 -9.900000 -9.900000 105.000000 272.000000 0.082000 0.080000 0.644000 0.552000 0.401000 0.346000 pga 0.447300 0.485600 0.245900 0.453900 1.431000 0.050530 -0.166200 5.500000 -1.134000 0.191700 -0.008088 4.500000 0.000000 -0.600000 1500.000000 -0.150000 -0.007010 -9.900000 -9.900000 110.000000 270.000000 0.100000 0.070000 0.695000 0.495000 0.398000 0.348000 0.010 0.453400 0.491600 0.251900 0.459900 1.421000 0.049320 -0.165900 5.500000 -1.134000 0.191600 -0.008088 4.500000 0.000000 -0.603720 1500.200000 -0.148330 -0.007010 -9.900000 -9.900000 111.670000 270.000000 0.096000 0.070000 0.698000 0.499000 0.402000 0.345000 0.020 0.485980 0.523590 0.297070 0.488750 1.433100 0.053388 -0.165610 5.500000 -1.139400 0.189620 -0.008074 4.500000 0.000000 -0.573880 1500.360000 -0.147100 -0.007280 -9.900000 -9.900000 113.100000 270.000000 0.092000 0.030000 0.702000 0.502000 0.409000 0.346000 0.022 0.498660 0.536470 0.313470 0.499730 1.433600 0.054888 -0.165200 5.500000 -1.140500 0.189240 -0.008095 4.500000 0.000000 -0.566750 1500.680000 -0.148010 -0.007320 -9.900000 -9.900000 113.370000 270.000000 0.088000 0.027000 0.707000 0.505000 0.418000 0.349000 0.025 0.522830 0.561300 0.344260 0.519990 1.432800 0.057529 -0.164990 5.500000 -1.141900 0.188750 -0.008153 4.500000 0.000000 -0.555200 1501.040000 -0.150150 -0.007360 -9.900000 -9.900000 113.070000 270.000000 0.086000 0.026000 0.711000 0.508000 0.427000 0.354000 0.029 0.559490 0.599230 0.391460 0.549950 1.427900 0.060732 -0.166320 5.500000 -1.142300 0.188440 -0.008290 4.500000 0.000000 -0.538500 1501.260000 -0.153870 -0.007370 -9.900000 -9.900000 112.360000 270.000000 0.084000 0.028000 0.716000 0.510000 0.436000 0.359000 0.030 0.569160 0.609200 0.403910 0.557830 1.426100 0.061444 -0.166900 5.500000 -1.142100 0.188420 -0.008336 4.490000 0.000000 -0.534140 1502.950000 -0.154850 -0.007350 -9.900000 -9.900000 112.130000 270.000000 0.081000 0.029000 0.721000 0.514000 0.445000 0.364000 0.032 0.588020 0.628750 0.427880 0.573300 1.422700 0.062806 -0.168130 5.500000 -1.141200 0.188400 -0.008445 4.450000 0.000000 -0.525290 1503.120000 -0.156850 -0.007310 -9.900000 -9.900000 111.650000 270.000000 0.078000 0.030000 0.726000 0.516000 0.454000 0.369000 0.035 0.616360 0.658180 0.462520 0.597040 1.417400 0.064559 -0.170150 5.500000 -1.138800 0.188390 -0.008642 4.400000 0.000000 -0.511920 1503.240000 -0.160160 -0.007210 -9.900000 -9.900000 110.640000 270.000000 0.077000 0.031000 0.730000 0.518000 0.462000 0.374000 0.036 0.625540 0.667720 0.473380 0.604960 1.415800 0.065028 -0.170830 5.500000 -1.137800 0.188370 -0.008715 4.380000 0.000000 -0.507520 1503.320000 -0.161420 -0.007170 -9.900000 -9.900000 109.530000 270.000000 0.075000 0.031000 0.734000 0.520000 0.470000 0.379000 0.040 0.662810 0.706040 0.515320 0.638280 1.409000 0.066183 -0.173570 5.500000 -1.132400 0.188160 -0.009030 4.320000 0.000000 -0.490650 1503.350000 -0.167770 -0.006980 -9.900000 -9.900000 108.280000 270.000000 0.073000 0.032000 0.738000 0.521000 0.478000 0.384000 0.042 0.680870 0.724430 0.534450 0.655050 1.405900 0.066438 -0.174850 5.500000 -1.129200 0.187970 -0.009195 4.290000 0.000000 -0.482900 1503.340000 -0.171930 -0.006870 -9.900000 -9.900000 106.990000 270.000000 0.072000 0.032000 0.742000 0.523000 0.484000 0.390000 0.044 0.698820 0.742770 0.552820 0.672250 1.403300 0.066663 -0.176190 5.500000 -1.125900 0.187750 -0.009360 4.270000 0.000000 -0.475720 1503.130000 -0.176640 -0.006770 -9.900000 -9.900000 105.410000 270.000000 0.070000 0.031000 0.745000 0.525000 0.490000 0.397000 0.045 0.708220 0.752320 0.562220 0.681390 1.402100 0.066774 -0.176930 5.500000 -1.124200 0.187640 -0.009441 4.250000 0.000000 -0.472360 1502.840000 -0.179140 -0.006720 -9.900000 -9.900000 103.610000 270.000000 0.069000 0.031000 0.748000 0.527000 0.496000 0.405000 0.046 0.717790 0.762020 0.571660 0.690760 1.400900 0.066891 -0.177690 5.500000 -1.122400 0.187520 -0.009521 4.240000 0.000000 -0.469150 1502.470000 -0.181700 -0.006670 -9.900000 -9.900000 101.700000 270.000000 0.067000 0.031000 0.750000 0.529000 0.499000 0.412000 0.048 0.735740 0.780150 0.588880 0.708540 1.399100 0.067127 -0.179200 5.500000 -1.119200 0.187300 -0.009676 4.220000 0.000000 -0.463210 1502.010000 -0.186880 -0.006560 -9.900000 -9.900000 99.760000 270.000000 0.065000 0.031000 0.752000 0.530000 0.502000 0.419000 0.050 0.754360 0.799050 0.606520 0.727260 1.397400 0.067357 -0.180820 5.500000 -1.115900 0.187090 -0.009819 4.200000 0.000000 -0.457950 1501.420000 -0.192000 -0.006470 -9.900000 -9.900000 97.930000 270.000000 0.063000 0.030000 0.753000 0.532000 0.503000 0.426000 0.055 0.799600 0.844500 0.647700 0.773700 1.394700 0.067797 -0.184800 5.500000 -1.108200 0.186550 -0.010120 4.150000 0.000000 -0.447870 1500.710000 -0.203690 -0.006250 -9.900000 -9.900000 96.030000 270.000000 0.062000 0.029000 0.753000 0.534000 0.502000 0.434000 0.060 0.843940 0.888840 0.685620 0.820670 1.395400 0.068591 -0.188580 5.500000 -1.100900 0.185820 -0.010330 4.110000 0.000000 -0.441860 1499.830000 -0.213740 -0.006070 -9.900000 -9.900000 94.100000 270.010000 0.061000 0.027000 0.753000 0.536000 0.499000 0.441000 0.065 0.886550 0.931160 0.719410 0.867240 1.400400 0.070127 -0.191760 5.500000 -1.094200 0.184850 -0.010480 4.080000 0.000000 -0.439510 1498.740000 -0.222250 -0.005930 -9.900000 -9.900000 92.080000 270.020000 0.061000 0.025000 0.752000 0.538000 0.495000 0.448000 0.067 0.902700 0.947110 0.731710 0.885260 1.403200 0.070895 -0.192910 5.500000 -1.091800 0.184420 -0.010520 4.070000 0.000000 -0.439500 1497.420000 -0.225240 -0.005880 -9.900000 -9.900000 90.010000 270.020000 0.061000 0.025000 0.750000 0.540000 0.489000 0.455000 0.070 0.926520 0.970570 0.749400 0.912270 1.408200 0.072075 -0.194510 5.500000 -1.088400 0.183690 -0.010560 4.060000 0.000000 -0.440400 1495.850000 -0.229310 -0.005820 -9.900000 -9.900000 87.970000 270.030000 0.062000 0.024000 0.748000 0.541000 0.483000 0.461000 0.075 0.964470 1.007700 0.776780 0.956300 1.417400 0.073549 -0.196650 5.500000 -1.083100 0.182250 -0.010580 4.040000 0.000000 -0.444110 1494.000000 -0.235000 -0.005730 -9.900000 -9.900000 85.990000 270.040000 0.064000 0.022000 0.745000 0.542000 0.474000 0.466000 0.080 1.000300 1.042600 0.801610 0.998180 1.426100 0.073735 -0.198160 5.500000 -1.078500 0.180520 -0.010560 4.020000 0.000000 -0.450200 1491.820000 -0.239440 -0.005670 -9.900000 -9.900000 84.230000 270.050000 0.067000 0.020000 0.741000 0.543000 0.464000 0.468000 0.085 1.034000 1.075500 0.824230 1.037900 1.432200 0.071940 -0.199020 5.510000 -1.074500 0.178560 -0.010510 4.030000 0.000000 -0.458130 1489.290000 -0.242850 -0.005630 -9.900000 -9.900000 82.740000 270.060000 0.072000 0.019000 0.737000 0.543000 0.452000 0.468000 0.090 1.066600 1.107600 0.845910 1.076200 1.435000 0.068097 -0.199290 5.520000 -1.070900 0.176430 -0.010420 4.070000 0.000000 -0.467320 1486.360000 -0.245440 -0.005610 -9.900000 -9.900000 81.540000 270.070000 0.076000 0.017000 0.734000 0.542000 0.440000 0.466000 0.095 1.098100 1.138500 0.867030 1.112700 1.433900 0.062327 -0.199000 5.530000 -1.067800 0.174200 -0.010320 4.100000 0.000000 -0.477210 1482.980000 -0.247470 -0.005600 -9.900000 -9.900000 80.460000 270.080000 0.082000 0.016000 0.731000 0.542000 0.428000 0.464000 0.100 1.126800 1.166900 0.887100 1.145400 1.429300 0.055231 -0.198380 5.540000 -1.065200 0.172030 -0.010200 4.130000 0.000000 -0.487240 1479.120000 -0.249160 -0.005600 -9.900000 -9.900000 79.590000 270.090000 0.087000 0.014000 0.728000 0.541000 0.415000 0.458000 0.110 1.178500 1.217900 0.927020 1.203000 1.411000 0.037389 -0.196010 5.570000 -1.060700 0.167700 -0.009964 4.190000 0.000000 -0.506320 1474.740000 -0.252130 -0.005620 -9.900000 -9.900000 79.050000 270.110000 0.093000 0.012000 0.726000 0.540000 0.403000 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0.000000 -0.978260 857.070000 -0.004702 -0.001520 1.253400 0.609180 129.490000 195.010000 0.072000 0.000000 0.536000 0.616000 0.543000 0.349000 4.000 -1.638800 -1.574800 -1.667300 -1.751600 2.204000 -0.014642 0.763030 6.200000 -1.216200 0.102180 -0.000052 7.320000 0.000000 -0.969380 844.480000 -0.003212 -0.001520 1.271100 0.629390 129.490000 199.450000 0.070000 0.000000 0.536000 0.616000 0.543000 0.349000 4.200 -1.711600 -1.643900 -1.745100 -1.829000 2.212300 -0.012248 0.785520 6.200000 -1.216500 0.102690 -0.000047 7.390000 0.000000 -0.960120 832.450000 -0.002103 -0.001520 1.287000 0.651570 129.570000 204.930000 0.068000 0.000000 0.535000 0.616000 0.542000 0.349000 4.400 -1.779800 -1.708900 -1.819200 -1.901100 2.218100 -0.011459 0.807920 6.200000 -1.216900 0.103040 -0.000039 7.460000 0.000000 -0.950490 821.180000 -0.001324 -0.001500 1.300400 0.674210 129.710000 211.090000 0.066000 0.000000 0.534000 0.617000 0.540000 0.347000 4.600 -1.846900 -1.773100 -1.892300 -1.971200 2.223000 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0.329000 6.000 -2.242100 -2.156300 -2.365900 -2.357900 2.237700 -0.026383 0.948700 6.200000 -1.223200 0.107500 0.000000 8.480000 0.000000 -0.862860 779.910000 0.000188 -0.001380 1.349600 0.802780 130.530000 249.340000 0.059000 0.000000 0.524000 0.625000 0.524000 0.321000 6.500 -2.368600 -2.278500 -2.532200 -2.477000 2.215000 -0.039505 0.976430 6.200000 -1.229900 0.112310 0.000000 8.900000 0.000000 -0.833550 775.600000 0.000159 -0.001370 1.348900 0.814800 130.630000 252.940000 0.059000 0.000000 0.520000 0.634000 0.517000 0.312000 7.000 -2.482700 -2.388100 -2.681800 -2.585400 2.172000 -0.059140 0.997570 6.200000 -1.240800 0.118530 0.000000 9.200000 0.000000 -0.804570 772.680000 0.000056 -0.001370 1.342200 0.816150 130.700000 253.120000 0.059000 0.000000 0.515000 0.636000 0.514000 0.302000 7.500 -2.586500 -2.487400 -2.817600 -2.685400 2.118700 -0.081606 1.012100 6.200000 -1.254300 0.125070 0.000000 9.480000 0.000000 -0.776650 771.010000 -0.000055 -0.001370 1.328800 0.809000 130.720000 250.390000 0.058000 0.000000 0.512000 0.634000 0.511000 0.270000 8.000 -2.686100 -2.582900 -2.943800 -2.782300 2.061300 -0.103820 1.023200 6.200000 -1.268800 0.131460 0.000000 9.570000 0.000000 -0.750330 760.810000 -0.000117 -0.001370 1.308400 0.795380 130.870000 245.230000 0.059000 0.000000 0.510000 0.630000 0.507000 0.278000 8.500 -2.782000 -2.675200 -3.059700 -2.877600 2.008400 -0.121140 1.033500 6.200000 -1.283900 0.137420 0.000000 9.620000 0.000000 -0.725440 764.500000 -0.000131 -0.001370 1.282200 0.776710 130.710000 238.130000 0.059000 0.000000 0.509000 0.622000 0.503000 0.265000 9.000 -2.879200 -2.768700 -3.171300 -2.975900 1.960500 -0.134070 1.045300 6.200000 -1.298900 0.142940 0.000000 9.660000 0.000000 -0.701610 768.070000 -0.000108 -0.001370 1.251500 0.754250 130.500000 229.560000 0.060000 0.000000 0.509000 0.613000 0.498000 0.252000 9.500 -2.976900 -2.863400 -3.278500 -3.076000 1.918900 -0.143640 1.056700 6.200000 -1.313000 0.147810 0.000000 9.660000 0.000000 -0.678500 771.550000 -0.000060 -0.001360 1.217900 0.729250 130.260000 220.020000 0.060000 0.000000 0.509000 0.604000 0.492000 0.239000 10.00 -3.070200 -2.953700 -3.377600 -3.172600 1.883700 -0.150960 1.065100 6.200000 -1.325300 0.151830 0.000000 9.660000 0.000000 -0.655750 775.000000 0.000000 -0.001360 1.182900 0.703000 130.000000 210.000000 0.060000 0.000000 0.510000 0.604000 0.487000 0.239000 """) CONSTS = { "Mref": 4.5, "Rref": 1.0, "Vref": 760.0, "f1": 0.0, "f3": 0.1, "v1": 225.0, "v2": 300.0}
[docs]class BooreEtAl2014HighQ(BooreEtAl2014): """ This class implements the Boore et al. (2014) model considering the correction to the path scaling term for High Q regions (e.g. China and Turkey) The modification is made to the "Dc3" coefficient """ COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT e0 e1 e2 e3 e4 e5 e6 Mh c1 c2 c3 h Dc3 c Vc f4 f5 f6 f7 R1 R2 DfR DfV f1 f2 t1 t2 pgv 5.037000 5.078000 4.849000 5.033000 1.073000 -0.153600 0.225200 6.200000 -1.243000 0.148900 -0.003440 5.300000 0.004345 -0.840000 1300.000000 -0.100000 -0.008440 -9.900000 -9.900000 105.000000 272.000000 0.082000 0.080000 0.644000 0.552000 0.401000 0.346000 pga 0.447300 0.485600 0.245900 0.453900 1.431000 0.050530 -0.166200 5.500000 -1.134000 0.191700 -0.008088 4.500000 0.002858 -0.600000 1500.000000 -0.150000 -0.007010 -9.900000 -9.900000 110.000000 270.000000 0.100000 0.070000 0.695000 0.495000 0.398000 0.348000 0.010 0.453400 0.491600 0.251900 0.459900 1.421000 0.049320 -0.165900 5.500000 -1.134000 0.191600 -0.008088 4.500000 0.002816 -0.603720 1500.200000 -0.148330 -0.007010 -9.900000 -9.900000 111.670000 270.000000 0.096000 0.070000 0.698000 0.499000 0.402000 0.345000 0.020 0.485980 0.523590 0.297070 0.488750 1.433100 0.053388 -0.165610 5.500000 -1.139400 0.189620 -0.008074 4.500000 0.002780 -0.573880 1500.360000 -0.147100 -0.007280 -9.900000 -9.900000 113.100000 270.000000 0.092000 0.030000 0.702000 0.502000 0.409000 0.346000 0.022 0.498660 0.536470 0.313470 0.499730 1.433600 0.054888 -0.165200 5.500000 -1.140500 0.189240 -0.008095 4.500000 0.002760 -0.566750 1500.680000 -0.148010 -0.007320 -9.900000 -9.900000 113.370000 270.000000 0.088000 0.027000 0.707000 0.505000 0.418000 0.349000 0.025 0.522830 0.561300 0.344260 0.519990 1.432800 0.057529 -0.164990 5.500000 -1.141900 0.188750 -0.008153 4.500000 0.002754 -0.555200 1501.040000 -0.150150 -0.007360 -9.900000 -9.900000 113.070000 270.000000 0.086000 0.026000 0.711000 0.508000 0.427000 0.354000 0.029 0.559490 0.599230 0.391460 0.549950 1.427900 0.060732 -0.166320 5.500000 -1.142300 0.188440 -0.008290 4.500000 0.002762 -0.538500 1501.260000 -0.153870 -0.007370 -9.900000 -9.900000 112.360000 270.000000 0.084000 0.028000 0.716000 0.510000 0.436000 0.359000 0.030 0.569160 0.609200 0.403910 0.557830 1.426100 0.061444 -0.166900 5.500000 -1.142100 0.188420 -0.008336 4.490000 0.002765 -0.534140 1502.950000 -0.154850 -0.007350 -9.900000 -9.900000 112.130000 270.000000 0.081000 0.029000 0.721000 0.514000 0.445000 0.364000 0.032 0.588020 0.628750 0.427880 0.573300 1.422700 0.062806 -0.168130 5.500000 -1.141200 0.188400 -0.008445 4.450000 0.002769 -0.525290 1503.120000 -0.156850 -0.007310 -9.900000 -9.900000 111.650000 270.000000 0.078000 0.030000 0.726000 0.516000 0.454000 0.369000 0.035 0.616360 0.658180 0.462520 0.597040 1.417400 0.064559 -0.170150 5.500000 -1.138800 0.188390 -0.008642 4.400000 0.002784 -0.511920 1503.240000 -0.160160 -0.007210 -9.900000 -9.900000 110.640000 270.000000 0.077000 0.031000 0.730000 0.518000 0.462000 0.374000 0.036 0.625540 0.667720 0.473380 0.604960 1.415800 0.065028 -0.170830 5.500000 -1.137800 0.188370 -0.008715 4.380000 0.002801 -0.507520 1503.320000 -0.161420 -0.007170 -9.900000 -9.900000 109.530000 270.000000 0.075000 0.031000 0.734000 0.520000 0.470000 0.379000 0.040 0.662810 0.706040 0.515320 0.638280 1.409000 0.066183 -0.173570 5.500000 -1.132400 0.188160 -0.009030 4.320000 0.002822 -0.490650 1503.350000 -0.167770 -0.006980 -9.900000 -9.900000 108.280000 270.000000 0.073000 0.032000 0.738000 0.521000 0.478000 0.384000 0.042 0.680870 0.724430 0.534450 0.655050 1.405900 0.066438 -0.174850 5.500000 -1.129200 0.187970 -0.009195 4.290000 0.002847 -0.482900 1503.340000 -0.171930 -0.006870 -9.900000 -9.900000 106.990000 270.000000 0.072000 0.032000 0.742000 0.523000 0.484000 0.390000 0.044 0.698820 0.742770 0.552820 0.672250 1.403300 0.066663 -0.176190 5.500000 -1.125900 0.187750 -0.009360 4.270000 0.002874 -0.475720 1503.130000 -0.176640 -0.006770 -9.900000 -9.900000 105.410000 270.000000 0.070000 0.031000 0.745000 0.525000 0.490000 0.397000 0.045 0.708220 0.752320 0.562220 0.681390 1.402100 0.066774 -0.176930 5.500000 -1.124200 0.187640 -0.009441 4.250000 0.002900 -0.472360 1502.840000 -0.179140 -0.006720 -9.900000 -9.900000 103.610000 270.000000 0.069000 0.031000 0.748000 0.527000 0.496000 0.405000 0.046 0.717790 0.762020 0.571660 0.690760 1.400900 0.066891 -0.177690 5.500000 -1.122400 0.187520 -0.009521 4.240000 0.002923 -0.469150 1502.470000 -0.181700 -0.006670 -9.900000 -9.900000 101.700000 270.000000 0.067000 0.031000 0.750000 0.529000 0.499000 0.412000 0.048 0.735740 0.780150 0.588880 0.708540 1.399100 0.067127 -0.179200 5.500000 -1.119200 0.187300 -0.009676 4.220000 0.002944 -0.463210 1502.010000 -0.186880 -0.006560 -9.900000 -9.900000 99.760000 270.000000 0.065000 0.031000 0.752000 0.530000 0.502000 0.419000 0.050 0.754360 0.799050 0.606520 0.727260 1.397400 0.067357 -0.180820 5.500000 -1.115900 0.187090 -0.009819 4.200000 0.002957 -0.457950 1501.420000 -0.192000 -0.006470 -9.900000 -9.900000 97.930000 270.000000 0.063000 0.030000 0.753000 0.532000 0.503000 0.426000 0.055 0.799600 0.844500 0.647700 0.773700 1.394700 0.067797 -0.184800 5.500000 -1.108200 0.186550 -0.010120 4.150000 0.002964 -0.447870 1500.710000 -0.203690 -0.006250 -9.900000 -9.900000 96.030000 270.000000 0.062000 0.029000 0.753000 0.534000 0.502000 0.434000 0.060 0.843940 0.888840 0.685620 0.820670 1.395400 0.068591 -0.188580 5.500000 -1.100900 0.185820 -0.010330 4.110000 0.002968 -0.441860 1499.830000 -0.213740 -0.006070 -9.900000 -9.900000 94.100000 270.010000 0.061000 0.027000 0.753000 0.536000 0.499000 0.441000 0.065 0.886550 0.931160 0.719410 0.867240 1.400400 0.070127 -0.191760 5.500000 -1.094200 0.184850 -0.010480 4.080000 0.002968 -0.439510 1498.740000 -0.222250 -0.005930 -9.900000 -9.900000 92.080000 270.020000 0.061000 0.025000 0.752000 0.538000 0.495000 0.448000 0.067 0.902700 0.947110 0.731710 0.885260 1.403200 0.070895 -0.192910 5.500000 -1.091800 0.184420 -0.010520 4.070000 0.002968 -0.439500 1497.420000 -0.225240 -0.005880 -9.900000 -9.900000 90.010000 270.020000 0.061000 0.025000 0.750000 0.540000 0.489000 0.455000 0.070 0.926520 0.970570 0.749400 0.912270 1.408200 0.072075 -0.194510 5.500000 -1.088400 0.183690 -0.010560 4.060000 0.002964 -0.440400 1495.850000 -0.229310 -0.005820 -9.900000 -9.900000 87.970000 270.030000 0.062000 0.024000 0.748000 0.541000 0.483000 0.461000 0.075 0.964470 1.007700 0.776780 0.956300 1.417400 0.073549 -0.196650 5.500000 -1.083100 0.182250 -0.010580 4.040000 0.002957 -0.444110 1494.000000 -0.235000 -0.005730 -9.900000 -9.900000 85.990000 270.040000 0.064000 0.022000 0.745000 0.542000 0.474000 0.466000 0.080 1.000300 1.042600 0.801610 0.998180 1.426100 0.073735 -0.198160 5.500000 -1.078500 0.180520 -0.010560 4.020000 0.002945 -0.450200 1491.820000 -0.239440 -0.005670 -9.900000 -9.900000 84.230000 270.050000 0.067000 0.020000 0.741000 0.543000 0.464000 0.468000 0.085 1.034000 1.075500 0.824230 1.037900 1.432200 0.071940 -0.199020 5.510000 -1.074500 0.178560 -0.010510 4.030000 0.002930 -0.458130 1489.290000 -0.242850 -0.005630 -9.900000 -9.900000 82.740000 270.060000 0.072000 0.019000 0.737000 0.543000 0.452000 0.468000 0.090 1.066600 1.107600 0.845910 1.076200 1.435000 0.068097 -0.199290 5.520000 -1.070900 0.176430 -0.010420 4.070000 0.002914 -0.467320 1486.360000 -0.245440 -0.005610 -9.900000 -9.900000 81.540000 270.070000 0.076000 0.017000 0.734000 0.542000 0.440000 0.466000 0.095 1.098100 1.138500 0.867030 1.112700 1.433900 0.062327 -0.199000 5.530000 -1.067800 0.174200 -0.010320 4.100000 0.002897 -0.477210 1482.980000 -0.247470 -0.005600 -9.900000 -9.900000 80.460000 270.080000 0.082000 0.016000 0.731000 0.542000 0.428000 0.464000 0.100 1.126800 1.166900 0.887100 1.145400 1.429300 0.055231 -0.198380 5.540000 -1.065200 0.172030 -0.010200 4.130000 0.002879 -0.487240 1479.120000 -0.249160 -0.005600 -9.900000 -9.900000 79.590000 270.090000 0.087000 0.014000 0.728000 0.541000 0.415000 0.458000 0.110 1.178500 1.217900 0.927020 1.203000 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-0.001540 1.233600 0.589320 129.560000 191.980000 0.075000 0.000000 0.536000 0.616000 0.542000 0.348000 3.800 -1.561700 -1.501400 -1.586500 -1.668500 2.193800 -0.018362 0.740280 6.200000 -1.215800 0.101420 -0.000053 7.240000 0.002586 -0.978260 857.070000 -0.004702 -0.001520 1.253400 0.609180 129.490000 195.010000 0.072000 0.000000 0.536000 0.616000 0.543000 0.349000 4.000 -1.638800 -1.574800 -1.667300 -1.751600 2.204000 -0.014642 0.763030 6.200000 -1.216200 0.102180 -0.000052 7.320000 0.002605 -0.969380 844.480000 -0.003212 -0.001520 1.271100 0.629390 129.490000 199.450000 0.070000 0.000000 0.536000 0.616000 0.543000 0.349000 4.200 -1.711600 -1.643900 -1.745100 -1.829000 2.212300 -0.012248 0.785520 6.200000 -1.216500 0.102690 -0.000047 7.390000 0.002619 -0.960120 832.450000 -0.002103 -0.001520 1.287000 0.651570 129.570000 204.930000 0.068000 0.000000 0.535000 0.616000 0.542000 0.349000 4.400 -1.779800 -1.708900 -1.819200 -1.901100 2.218100 -0.011459 0.807920 6.200000 -1.216900 0.103040 -0.000039 7.460000 0.002624 -0.950490 821.180000 -0.001324 -0.001500 1.300400 0.674210 129.710000 211.090000 0.066000 0.000000 0.534000 0.617000 0.540000 0.347000 4.600 -1.846900 -1.773100 -1.892300 -1.971200 2.223000 -0.011760 0.831260 6.200000 -1.217500 0.103240 -0.000027 7.520000 0.002622 -0.940500 810.790000 -0.000804 -0.001480 1.312500 0.696980 129.870000 217.560000 0.064000 0.000000 0.533000 0.619000 0.538000 0.345000 4.800 -1.906300 -1.830300 -1.957300 -2.032600 2.226800 -0.012879 0.852400 6.200000 -1.218200 0.103370 -0.000014 7.640000 0.002615 -0.930180 801.410000 -0.000471 -0.001460 1.322500 0.718880 130.050000 223.990000 0.063000 0.000000 0.531000 0.621000 0.535000 0.341000 5.000 -1.966000 -1.888200 -2.024500 -2.092800 2.229900 -0.014855 0.873140 6.200000 -1.218900 0.103530 0.000000 7.780000 0.002604 -0.919540 793.130000 -0.000255 -0.001440 1.328900 0.738060 130.220000 230.000000 0.061000 0.000000 0.528000 0.622000 0.532000 0.335000 5.500 -2.105100 -2.023200 -2.190800 -2.228800 2.238900 -0.019502 0.914660 6.200000 -1.220400 0.104600 0.000000 8.070000 0.002591 -0.891760 785.730000 0.000072 -0.001400 1.345000 0.777900 130.390000 241.860000 0.060000 0.000000 0.526000 0.624000 0.528000 0.329000 6.000 -2.242100 -2.156300 -2.365900 -2.357900 2.237700 -0.026383 0.948700 6.200000 -1.223200 0.107500 0.000000 8.480000 0.002584 -0.862860 779.910000 0.000188 -0.001380 1.349600 0.802780 130.530000 249.340000 0.059000 0.000000 0.524000 0.625000 0.524000 0.321000 6.500 -2.368600 -2.278500 -2.532200 -2.477000 2.215000 -0.039505 0.976430 6.200000 -1.229900 0.112310 0.000000 8.900000 0.002586 -0.833550 775.600000 0.000159 -0.001370 1.348900 0.814800 130.630000 252.940000 0.059000 0.000000 0.520000 0.634000 0.517000 0.312000 7.000 -2.482700 -2.388100 -2.681800 -2.585400 2.172000 -0.059140 0.997570 6.200000 -1.240800 0.118530 0.000000 9.200000 0.002603 -0.804570 772.680000 0.000056 -0.001370 1.342200 0.816150 130.700000 253.120000 0.059000 0.000000 0.515000 0.636000 0.514000 0.302000 7.500 -2.586500 -2.487400 -2.817600 -2.685400 2.118700 -0.081606 1.012100 6.200000 -1.254300 0.125070 0.000000 9.480000 0.002600 -0.776650 771.010000 -0.000055 -0.001370 1.328800 0.809000 130.720000 250.390000 0.058000 0.000000 0.512000 0.634000 0.511000 0.270000 8.000 -2.686100 -2.582900 -2.943800 -2.782300 2.061300 -0.103820 1.023200 6.200000 -1.268800 0.131460 0.000000 9.570000 0.002630 -0.750330 760.810000 -0.000117 -0.001370 1.308400 0.795380 130.870000 245.230000 0.059000 0.000000 0.510000 0.630000 0.507000 0.278000 8.500 -2.782000 -2.675200 -3.059700 -2.877600 2.008400 -0.121140 1.033500 6.200000 -1.283900 0.137420 0.000000 9.620000 0.002670 -0.725440 764.500000 -0.000131 -0.001370 1.282200 0.776710 130.710000 238.130000 0.059000 0.000000 0.509000 0.622000 0.503000 0.265000 9.000 -2.879200 -2.768700 -3.171300 -2.975900 1.960500 -0.134070 1.045300 6.200000 -1.298900 0.142940 0.000000 9.660000 0.002760 -0.701610 768.070000 -0.000108 -0.001370 1.251500 0.754250 130.500000 229.560000 0.060000 0.000000 0.509000 0.613000 0.498000 0.252000 9.500 -2.976900 -2.863400 -3.278500 -3.076000 1.918900 -0.143640 1.056700 6.200000 -1.313000 0.147810 0.000000 9.660000 0.002890 -0.678500 771.550000 -0.000060 -0.001360 1.217900 0.729250 130.260000 220.020000 0.060000 0.000000 0.509000 0.604000 0.492000 0.239000 10.00 -3.070200 -2.953700 -3.377600 -3.172600 1.883700 -0.150960 1.065100 6.200000 -1.325300 0.151830 0.000000 9.660000 0.003030 -0.655750 775.000000 0.000000 -0.001360 1.182900 0.703000 130.000000 210.000000 0.060000 0.000000 0.510000 0.604000 0.487000 0.239000 """)
[docs]class BooreEtAl2014LowQ(BooreEtAl2014): """ This class implements the Boore et al. (2014) model considering the correction to the path scaling term for Low Q regions (e.g. Italy and Japan) The modification is made to the "Dc3" coefficient """ COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT e0 e1 e2 e3 e4 e5 e6 Mh c1 c2 c3 h Dc3 c Vc f4 f5 f6 f7 R1 R2 DfR DfV f1 f2 t1 t2 pgv 5.037000 5.078000 4.849000 5.033000 1.073000 -0.153600 0.225200 6.20 -1.243000 0.148900 -0.003440 5.30 -0.0003300 -0.840000 1300.00 -0.100000 -0.008440 -9.900 -9.900 105.000 272.000 0.082 0.080 0.644 0.552 0.401 0.346 pga 0.447300 0.485600 0.245900 0.453900 1.431000 0.050530 -0.166200 5.50 -1.134000 0.191700 -0.008088 4.50 -0.0025500 -0.600000 1500.00 -0.150000 -0.007010 -9.900 -9.900 110.000 270.000 0.100 0.070 0.695 0.495 0.398 0.348 0.010 0.453400 0.491600 0.251900 0.459900 1.421000 0.049320 -0.165900 5.50 -1.134000 0.191600 -0.008088 4.50 -0.0024367 -0.603720 1500.20 -0.148330 -0.007010 -9.900 -9.900 111.670 270.000 0.096 0.070 0.698 0.499 0.402 0.345 0.020 0.485980 0.523590 0.297070 0.488750 1.433100 0.053388 -0.165610 5.50 -1.139400 0.189620 -0.008074 4.50 -0.0023400 -0.573880 1500.36 -0.147100 -0.007280 -9.900 -9.900 113.100 270.000 0.092 0.030 0.702 0.502 0.409 0.346 0.022 0.498660 0.536470 0.313470 0.499730 1.433600 0.054888 -0.165200 5.50 -1.140500 0.189240 -0.008095 4.50 -0.0022886 -0.566750 1500.68 -0.148010 -0.007320 -9.900 -9.900 113.370 270.000 0.088 0.027 0.707 0.505 0.418 0.349 0.025 0.522830 0.561300 0.344260 0.519990 1.432800 0.057529 -0.164990 5.50 -1.141900 0.188750 -0.008153 4.50 -0.0022500 -0.555200 1501.04 -0.150150 -0.007360 -9.900 -9.900 113.070 270.000 0.086 0.026 0.711 0.508 0.427 0.354 0.029 0.559490 0.599230 0.391460 0.549950 1.427900 0.060732 -0.166320 5.50 -1.142300 0.188440 -0.008290 4.50 -0.0022145 -0.538500 1501.26 -0.153870 -0.007370 -9.900 -9.900 112.360 270.000 0.084 0.028 0.716 0.510 0.436 0.359 0.030 0.569160 0.609200 0.403910 0.557830 1.426100 0.061444 -0.166900 5.50 -1.142100 0.188420 -0.008336 4.49 -0.0021676 -0.534140 1502.95 -0.154850 -0.007350 -9.900 -9.900 112.130 270.000 0.081 0.029 0.721 0.514 0.445 0.364 0.032 0.588020 0.628750 0.427880 0.573300 1.422700 0.062806 -0.168130 5.50 -1.141200 0.188400 -0.008445 4.45 -0.0021167 -0.525290 1503.12 -0.156850 -0.007310 -9.900 -9.900 111.650 270.000 0.078 0.030 0.726 0.516 0.454 0.369 0.035 0.616360 0.658180 0.462520 0.597040 1.417400 0.064559 -0.170150 5.50 -1.138800 0.188390 -0.008642 4.40 -0.0020957 -0.511920 1503.24 -0.160160 -0.007210 -9.900 -9.900 110.640 270.000 0.077 0.031 0.730 0.518 0.462 0.374 0.036 0.625540 0.667720 0.473380 0.604960 1.415800 0.065028 -0.170830 5.50 -1.137800 0.188370 -0.008715 4.38 -0.0020748 -0.507520 1503.32 -0.161420 -0.007170 -9.900 -9.900 109.530 270.000 0.075 0.031 0.734 0.520 0.470 0.379 0.040 0.662810 0.706040 0.515320 0.638280 1.409000 0.066183 -0.173570 5.50 -1.132400 0.188160 -0.009030 4.32 -0.0020539 -0.490650 1503.35 -0.167770 -0.006980 -9.900 -9.900 108.280 270.000 0.073 0.032 0.738 0.521 0.478 0.384 0.042 0.680870 0.724430 0.534450 0.655050 1.405900 0.066438 -0.174850 5.50 -1.129200 0.187970 -0.009195 4.29 -0.0020348 -0.482900 1503.34 -0.171930 -0.006870 -9.900 -9.900 106.990 270.000 0.072 0.032 0.742 0.523 0.484 0.390 0.044 0.698820 0.742770 0.552820 0.672250 1.403300 0.066663 -0.176190 5.50 -1.125900 0.187750 -0.009360 4.27 -0.0020157 -0.475720 1503.13 -0.176640 -0.006770 -9.900 -9.900 105.410 270.000 0.070 0.031 0.745 0.525 0.490 0.397 0.045 0.708220 0.752320 0.562220 0.681390 1.402100 0.066774 -0.176930 5.50 -1.124200 0.187640 -0.009441 4.25 -0.0020011 -0.472360 1502.84 -0.179140 -0.006720 -9.900 -9.900 103.610 270.000 0.069 0.031 0.748 0.527 0.496 0.405 0.046 0.717790 0.762020 0.571660 0.690760 1.400900 0.066891 -0.177690 5.50 -1.122400 0.187520 -0.009521 4.24 -0.0019929 -0.469150 1502.47 -0.181700 -0.006670 -9.900 -9.900 101.700 270.000 0.067 0.031 0.750 0.529 0.499 0.412 0.048 0.735740 0.780150 0.588880 0.708540 1.399100 0.067127 -0.179200 5.50 -1.119200 0.187300 -0.009676 4.22 -0.0019884 -0.463210 1502.01 -0.186880 -0.006560 -9.900 -9.900 99.760 270.000 0.065 0.031 0.752 0.530 0.502 0.419 0.050 0.754360 0.799050 0.606520 0.727260 1.397400 0.067357 -0.180820 5.50 -1.115900 0.187090 -0.009819 4.20 -0.0019911 -0.457950 1501.42 -0.192000 -0.006470 -9.900 -9.900 97.930 270.000 0.063 0.030 0.753 0.532 0.503 0.426 0.055 0.799600 0.844500 0.647700 0.773700 1.394700 0.067797 -0.184800 5.50 -1.108200 0.186550 -0.010120 4.15 -0.0020011 -0.447870 1500.71 -0.203690 -0.006250 -9.900 -9.900 96.030 270.000 0.062 0.029 0.753 0.534 0.502 0.434 0.060 0.843940 0.888840 0.685620 0.820670 1.395400 0.068591 -0.188580 5.50 -1.100900 0.185820 -0.010330 4.11 -0.0020193 -0.441860 1499.83 -0.213740 -0.006070 -9.900 -9.900 94.100 270.010 0.061 0.027 0.753 0.536 0.499 0.441 0.065 0.886550 0.931160 0.719410 0.867240 1.400400 0.070127 -0.191760 5.50 -1.094200 0.184850 -0.010480 4.08 -0.0020448 -0.439510 1498.74 -0.222250 -0.005930 -9.900 -9.900 92.080 270.020 0.061 0.025 0.752 0.538 0.495 0.448 0.067 0.902700 0.947110 0.731710 0.885260 1.403200 0.070895 -0.192910 5.50 -1.091800 0.184420 -0.010520 4.07 -0.0020766 -0.439500 1497.42 -0.225240 -0.005880 -9.900 -9.900 90.010 270.020 0.061 0.025 0.750 0.540 0.489 0.455 0.070 0.926520 0.970570 0.749400 0.912270 1.408200 0.072075 -0.194510 5.50 -1.088400 0.183690 -0.010560 4.06 -0.0021148 -0.440400 1495.85 -0.229310 -0.005820 -9.900 -9.900 87.970 270.030 0.062 0.024 0.748 0.541 0.483 0.461 0.075 0.964470 1.007700 0.776780 0.956300 1.417400 0.073549 -0.196650 5.50 -1.083100 0.182250 -0.010580 4.04 -0.0021594 -0.444110 1494.00 -0.235000 -0.005730 -9.900 -9.900 85.990 270.040 0.064 0.022 0.745 0.542 0.474 0.466 0.080 1.000300 1.042600 0.801610 0.998180 1.426100 0.073735 -0.198160 5.50 -1.078500 0.180520 -0.010560 4.02 -0.0022122 -0.450200 1491.82 -0.239440 -0.005670 -9.900 -9.900 84.230 270.050 0.067 0.020 0.741 0.543 0.464 0.468 0.085 1.034000 1.075500 0.824230 1.037900 1.432200 0.071940 -0.199020 5.51 -1.074500 0.178560 -0.010510 4.03 -0.0022695 -0.458130 1489.29 -0.242850 -0.005630 -9.900 -9.900 82.740 270.060 0.072 0.019 0.737 0.543 0.452 0.468 0.090 1.066600 1.107600 0.845910 1.076200 1.435000 0.068097 -0.199290 5.52 -1.070900 0.176430 -0.010420 4.07 -0.0023269 -0.467320 1486.36 -0.245440 -0.005610 -9.900 -9.900 81.540 270.070 0.076 0.017 0.734 0.542 0.440 0.466 0.095 1.098100 1.138500 0.867030 1.112700 1.433900 0.062327 -0.199000 5.53 -1.067800 0.174200 -0.010320 4.10 -0.0023833 -0.477210 1482.98 -0.247470 -0.005600 -9.900 -9.900 80.460 270.080 0.082 0.016 0.731 0.542 0.428 0.464 0.100 1.126800 1.166900 0.887100 1.145400 1.429300 0.055231 -0.198380 5.54 -1.065200 0.172030 -0.010200 4.13 -0.0024388 -0.487240 1479.12 -0.249160 -0.005600 -9.900 -9.900 79.590 270.090 0.087 0.014 0.728 0.541 0.415 0.458 0.110 1.178500 1.217900 0.927020 1.203000 1.411000 0.037389 -0.196010 5.57 -1.060700 0.167700 -0.009964 4.19 -0.0024916 -0.506320 1474.74 -0.252130 -0.005620 -9.900 -9.900 79.050 270.110 0.093 0.012 0.726 0.540 0.403 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-0.001440 1.329 0.738 130.220 230.000 0.061 0.000 0.528 0.622 0.532 0.335 5.500 -2.105100 -2.023200 -2.190800 -2.228800 2.238900 -0.019502 0.914660 6.20 -1.220400 0.104600 0.000000 8.07 -0.0004077 -0.891760 785.73 0.000072 -0.001400 1.345 0.778 130.390 241.860 0.060 0.000 0.526 0.624 0.528 0.329 6.000 -2.242100 -2.156300 -2.365900 -2.357900 2.237700 -0.026383 0.948700 6.20 -1.223200 0.107500 0.000000 8.48 -0.0002284 -0.862860 779.91 0.000188 -0.001380 1.350 0.803 130.530 249.340 0.059 0.000 0.524 0.625 0.524 0.321 6.500 -2.368600 -2.278500 -2.532200 -2.477000 2.215000 -0.039505 0.976430 6.20 -1.229900 0.112310 0.000000 8.90 -0.0000364 -0.833550 775.60 0.000159 -0.001370 1.349 0.815 130.630 252.940 0.059 0.000 0.520 0.634 0.517 0.312 7.000 -2.482700 -2.388100 -2.681800 -2.585400 2.172000 -0.059140 0.997570 6.20 -1.240800 0.118530 0.000000 9.20 0.0001684 -0.804570 772.68 0.000056 -0.001370 1.342 0.816 130.700 253.120 0.059 0.000 0.515 0.636 0.514 0.302 7.500 -2.586500 -2.487400 -2.817600 -2.685400 2.118700 -0.081606 1.012100 6.20 -1.254300 0.125070 0.000000 9.48 0.0003849 -0.776650 771.01 -0.000055 -0.001370 1.329 0.809 130.720 250.390 0.058 0.000 0.512 0.634 0.511 0.270 8.000 -2.686100 -2.582900 -2.943800 -2.782300 2.061300 -0.103820 1.023200 6.20 -1.268800 0.131460 0.000000 9.57 0.0007200 -0.750330 760.81 -0.000117 -0.001370 1.308 0.795 130.870 245.230 0.059 0.000 0.510 0.630 0.507 0.278 8.500 -2.782000 -2.675200 -3.059700 -2.877600 2.008400 -0.121140 1.033500 6.20 -1.283900 0.137420 0.000000 9.62 0.0009400 -0.725440 764.50 -0.000131 -0.001370 1.282 0.777 130.710 238.130 0.059 0.000 0.509 0.622 0.503 0.265 9.000 -2.879200 -2.768700 -3.171300 -2.975900 1.960500 -0.134070 1.045300 6.20 -1.298900 0.142940 0.000000 9.66 0.0011300 -0.701610 768.07 -0.000108 -0.001370 1.252 0.754 130.500 229.560 0.060 0.000 0.509 0.613 0.498 0.252 9.500 -2.976900 -2.863400 -3.278500 -3.076000 1.918900 -0.143640 1.056700 6.20 -1.313000 0.147810 0.000000 9.66 0.0013100 -0.678500 771.55 -0.000060 -0.001360 1.218 0.729 130.260 220.020 0.060 0.000 0.509 0.604 0.492 0.239 10.00 -3.070200 -2.953700 -3.377600 -3.172600 1.883700 -0.150960 1.065100 6.20 -1.325300 0.151830 0.000000 9.66 0.0014900 -0.655750 775.00 0.000000 -0.001360 1.183 0.703 130.000 210.000 0.060 0.000 0.510 0.604 0.487 0.239 """)
def california_basin_model(vs30): """ Returns the centred z1.0 (mu_z1) based on the California model (equation 11) """ coeff = 570.94 ** 4.0 model = (-7.15 / 4.0) * np.log( ((vs30 ** 4.0) + coeff) / ((1360.0 ** 4.0) + coeff) ) - np.log(1000.) return np.exp(model)
[docs]class BooreEtAl2014CaliforniaBasin(BooreEtAl2014): """ Implements the Boore et al. (2014) GMPE under the conditions that the global (average Q) attenuation model is preferred and the basin model is considered to be represented by the "California" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014HighQCaliforniaBasin(BooreEtAl2014HighQ): """ Implements the Boore et al. (2014) GMPE under the conditions that the high Q attenuation model is preferred and the basin model is considered to be represented by the "California" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014LowQCaliforniaBasin(BooreEtAl2014LowQ): """ Implements the Boore et al. (2014) GMPE under the conditions that the high Q attenuation model is preferred and the basin model is considered to be represented by the "California" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
def japan_basin_model(vs30): """ Returns the centred z1.0 (mu_z1) based on the Japan model (equation 12) """ coeff = 412.39 ** 2.0 model = (-5.23 / 2.0) * np.log( ((vs30 ** 2.0) + coeff) / ((1360.0 ** 2.0) + coeff) ) - np.log(1000.) return np.exp(model)
[docs]class BooreEtAl2014JapanBasin(BooreEtAl2014): """ Implements the Boore et al. (2014) GMPE under the conditions that the global (average Q) attenuation model is preferred and the basin model is considered to be represented by the "Japan" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014HighQJapanBasin(BooreEtAl2014HighQ): """ Implements the Boore et al. (2014) GMPE under the conditions that the high Q attenuation model is preferred and the basin model is considered to be represented by the "Japan" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014LowQJapanBasin(BooreEtAl2014LowQ): """ Implements the Boore et al. (2014) GMPE under the conditions that the low Q attenuation model is preferred and the basin model is considered to be represented by the "Japan" case """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014NoSOF(BooreEtAl2014): """ The Boore et al. (2014) GMPE can consider the case in which the style-of-faulting is unspecified. In this case the GMPE is no longer dependent on rake. """ #: Required rupture parameters are magnitude REQUIRES_RUPTURE_PARAMETERS = set(('mag',)) def _get_style_of_faulting_term(self, C, rup): """ Returns the coefficients of the "Unspecified" style-of-faulting """ return C["e0"]
[docs]class BooreEtAl2014HighQNoSOF(BooreEtAl2014HighQ): """ The Boore et al. (2014) GMPE, implemented for the High Q regions, for the case in which the style-of-faulting is unspecified. """ #: Required rupture parameters are magnitude REQUIRES_RUPTURE_PARAMETERS = set(('mag',)) def _get_style_of_faulting_term(self, C, rup): """ Returns the coefficients of the "Unspecified" style-of-faulting """ return C["e0"]
[docs]class BooreEtAl2014LowQNoSOF(BooreEtAl2014LowQ): """ The Boore et al. (2014) GMPE, implemented for the Low Q regions, for the case in which the style-of-faulting is unspecified. """ #: Required rupture parameters are magnitude REQUIRES_RUPTURE_PARAMETERS = set(('mag',)) def _get_style_of_faulting_term(self, C, rup): """ Returns the coefficients of the "Unspecified" style-of-faulting """ return C["e0"]
[docs]class BooreEtAl2014CaliforniaBasinNoSOF(BooreEtAl2014NoSOF): """ The Boore et al. (2014) GMPE, implemented for global (average Q) regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014HighQCaliforniaBasinNoSOF(BooreEtAl2014HighQNoSOF): """ The Boore et al. (2014) GMPE, implemented for high Q regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014LowQCaliforniaBasinNoSOF(BooreEtAl2014LowQNoSOF): """ The Boore et al. (2014) GMPE, implemented for high Q regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - california_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014JapanBasinNoSOF(BooreEtAl2014NoSOF): """ The Boore et al. (2014) GMPE, implemented for global (average Q) regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014HighQJapanBasinNoSOF(BooreEtAl2014HighQNoSOF): """ The Boore et al. (2014) GMPE, implemented for high Q regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1
[docs]class BooreEtAl2014LowQJapanBasinNoSOF(BooreEtAl2014LowQNoSOF): """ The Boore et al. (2014) GMPE, implemented for high Q regions, for the case when style of faulting is unspecficied and the California basin depth model is required """ #: Required site parameters are Vs30 and depth (in metres!) to 1 km/s #: shear-wave velocity layer REQUIRES_SITES_PARAMETERS = set(('vs30', 'z1pt0')) def _get_basin_depth_term(self, C, sites, period): """ In the case of the base model the basin depth term is switched off. Therefore we return an array of zeros. """ if period < 0.65: f_dz1 = np.zeros(len(sites.vs30), dtype=float) else: f_dz1 = C["f7"] + np.zeros(len(sites.vs30), dtype=float) f_ratio = C["f7"] / C["f6"] dz1 = (sites.z1pt0 / 1000.0) - japan_basin_model(sites.vs30) idx = dz1 <= f_ratio f_dz1[idx] = C["f6"] * dz1[idx] return f_dz1