Source code for openquake.hazardlib.gsim.berge_thierry_2003

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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"""
Module exports :class:`BergeThierryEtAl2003SIGMA`.
"""
import copy
import numpy as np
from scipy.constants import g

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


# TODO: Check whether lower validity bound is 4 or 7 km
[docs]class BergeThierryEtAl2003Ms(GMPE): """ Implements GMPE developed by Catherine Berge-Thierry, Fabrice Cotton, Oona Scoti, Daphne-Anne Griot-Pommera, and Yoshimitsu Fukushima and published as "New Empirical Response Spectral Attenuation Laws For Moderate European Earthquakes" (2003, Journal of Earthquake Engineering, 193-222) This class corresponds to the original formulation, usable with Ms. """ #: Supported tectonic region type is active shallow crust, see #: `Introduction`, page 194. DEFINED_FOR_TECTONIC_REGION_TYPE = const.TRT.ACTIVE_SHALLOW_CRUST #: Supported intensity measure types are spectral acceleration, and peak #: ground acceleration. The original manuscript provide coefficients only #: SA. For PGA, coefficients are assumed equal to the ones of SA for the #: smallest period (0.03 s) DEFINED_FOR_INTENSITY_MEASURE_TYPES = {PGA, SA} #: Supported intensity measure component is horizontal, see page 196. DEFINED_FOR_INTENSITY_MEASURE_COMPONENT = const.IMC.HORIZONTAL #: Supported standard deviation type is total, see table 3, page 203 DEFINED_FOR_STANDARD_DEVIATION_TYPES = {const.StdDev.TOTAL} #: Required site parameters is Vs30, used to distinguish between rock sites #: (Vs30 >= 800) m/s and alluvium sites (300 < Vs < 800), see section 2.2.3 #: page 201 REQUIRES_SITES_PARAMETERS = {'vs30'} #: Required rupture parameters is magnitude, see equation 1 page 201 REQUIRES_RUPTURE_PARAMETERS = {'mag'} #: Required distance measure is hypocentral distance, see equation 1 page #: 201 REQUIRES_DISTANCES = {'rhypo'}
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): return self._get_mean_and_stddevs(sites, rup, dists, imt, stddev_types)
def _get_stddevs(self, C, stddev_types, num_sites, mag_conversion_sigma): """ Return total standard deviation. """ assert all(stddev_type in self.DEFINED_FOR_STANDARD_DEVIATION_TYPES for stddev_type in stddev_types) sigma = np.zeros(num_sites) + C['sigma'] * np.log(10) sigma = np.sqrt(sigma ** 2 + (C['a'] ** 2) * ( mag_conversion_sigma ** 2)) stddevs = [sigma for _ in stddev_types] return stddevs def _get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types, mag_conversion_sigma=0.0): """ See :meth:`superclass method <.base.GroundShakingIntensityModel.get_mean_and_stddevs>` for spec of input and result values. """ # extract dictionaries of coefficients specific to required # intensity measure type C = self.COEFFS[imt] # clip distance at 4 km, minimum distance for which the equation is # valid (see section 2.2.4, page 201). This also avoids singularity # in the equation rhypo = np.array(dists.rhypo) # make a copy rhypo[rhypo < 4.] = 4. mean = C['a'] * rup.mag + C['b'] * rhypo - np.log10(rhypo) mean[sites.vs30 >= 800] += C['c1'] mean[sites.vs30 < 800] += C['c2'] # convert from log10 to ln, and from cm/s2 to g mean = mean * np.log(10) - 2 * np.log(10) - np.log(g) stddevs = self._get_stddevs(C, stddev_types, rhypo.shape[0], mag_conversion_sigma=mag_conversion_sigma) return mean, stddevs #: Coefficient tables are constructed from the electronic suplements of #: the original paper. Original coefficients in function of frequency. COEFFS = CoeffsTable(sa_damping=5, table="""\ IMT a b c1 c2 sigma pga 0.3118000 -0.0009303 1.537000 1.57300 0.2923 0.029412 0.3118000 -0.0009303 1.537000 1.57300 0.2923 0.030000 0.3114000 -0.0009334 1.541000 1.57600 0.2924 0.032258 0.3097000 -0.0009422 1.558000 1.58900 0.2928 0.034000 0.3083000 -0.0009547 1.573000 1.60200 0.2935 0.035714 0.3068000 -0.0009822 1.593000 1.61800 0.2947 0.040000 0.3033000 -0.0011190 1.653000 1.66500 0.2982 0.045455 0.3016000 -0.0012820 1.701000 1.70000 0.3015 0.050000 0.2992000 -0.0013410 1.740000 1.72900 0.3009 0.053000 0.2981000 -0.0014290 1.766000 1.74900 0.3022 0.055556 0.2969000 -0.0014320 1.785000 1.76500 0.3027 0.058824 0.2960000 -0.0014600 1.809000 1.78400 0.3040 0.059999 0.2960000 -0.0014720 1.814000 1.78800 0.3041 0.062500 0.2965000 -0.0015070 1.826000 1.79600 0.3047 0.064998 0.2944000 -0.0015150 1.851000 1.81700 0.3059 0.066667 0.2933000 -0.0015130 1.865000 1.82900 0.3059 0.068966 0.2924000 -0.0015460 1.881000 1.84200 0.3048 0.069999 0.2920000 -0.0015700 1.888000 1.84900 0.3046 0.071429 0.2909000 -0.0015830 1.901000 1.86100 0.3047 0.074074 0.2879000 -0.0015550 1.926000 1.88700 0.3059 0.075002 0.2871000 -0.0015400 1.933000 1.89300 0.3066 0.076923 0.2857000 -0.0015200 1.947000 1.90600 0.3072 0.080000 0.2866000 -0.0015310 1.954000 1.91100 0.3061 0.083333 0.2858000 -0.0015520 1.968000 1.92700 0.3058 0.084998 0.2856000 -0.0015830 1.976000 1.93500 0.3053 0.086957 0.2848000 -0.0015710 1.987000 1.94600 0.3042 0.090001 0.2819000 -0.0015360 2.011000 1.97300 0.3020 0.090909 0.2809000 -0.0015280 2.020000 1.98100 0.3016 0.095238 0.2781000 -0.0015430 2.054000 2.01000 0.3017 0.100000 0.2786000 -0.0014740 2.059000 2.01600 0.3019 0.105260 0.2776000 -0.0014220 2.072000 2.03400 0.3043 0.110000 0.2783000 -0.0014420 2.075000 2.04500 0.3073 0.111110 0.2783000 -0.0014380 2.077000 2.04700 0.3079 0.117650 0.2793000 -0.0014380 2.081000 2.05600 0.3103 0.120000 0.2806000 -0.0014360 2.076000 2.05400 0.3106 0.125000 0.2831000 -0.0014150 2.066000 2.05100 0.3121 0.129030 0.2863000 -0.0014400 2.052000 2.04200 0.3137 0.130010 0.2867000 -0.0014250 2.050000 2.04000 0.3142 0.133330 0.2887000 -0.0013970 2.040000 2.03300 0.3156 0.137930 0.2903000 -0.0013380 2.032000 2.02800 0.3161 0.140000 0.2915000 -0.0013220 2.027000 2.02200 0.3166 0.142860 0.2933000 -0.0013070 2.018000 2.01400 0.3173 0.148150 0.2950000 -0.0012560 2.009000 2.01000 0.3191 0.149990 0.2955000 -0.0012180 2.004000 2.00900 0.3196 0.153850 0.2955000 -0.0010520 1.997000 2.00700 0.3201 0.160000 0.2939000 -0.0008056 1.996000 2.01300 0.3200 0.166670 0.2952000 -0.0007097 1.989000 2.00600 0.3215 0.170010 0.2974000 -0.0006986 1.978000 1.99400 0.3230 0.173910 0.3016000 -0.0007341 1.957000 1.97000 0.3247 0.179990 0.3089000 -0.0007793 1.915000 1.93000 0.3267 0.181820 0.3109000 -0.0007826 1.901000 1.91900 0.3271 0.190010 0.3147000 -0.0007369 1.868000 1.89400 0.3262 0.190480 0.3149000 -0.0007337 1.867000 1.89300 0.3262 0.200000 0.3167000 -0.0006889 1.843000 1.88100 0.3250 0.208330 0.3196000 -0.0006719 1.814000 1.86100 0.3261 0.217390 0.3254000 -0.0006750 1.770000 1.82500 0.3281 0.219780 0.3271000 -0.0006918 1.758000 1.81500 0.3292 0.227270 0.3303000 -0.0006678 1.726000 1.79200 0.3320 0.238100 0.3340000 -0.0006171 1.683000 1.76200 0.3367 0.239980 0.3344000 -0.0005988 1.677000 1.75800 0.3371 0.250000 0.3365000 -0.0005750 1.651000 1.73600 0.3394 0.259740 0.3430000 -0.0007075 1.609000 1.69700 0.3422 0.263160 0.3442000 -0.0007200 1.599000 1.68800 0.3429 0.277780 0.3501000 -0.0007520 1.550000 1.64500 0.3444 0.280030 0.3511000 -0.0007530 1.542000 1.63800 0.3447 0.290020 0.3555000 -0.0007836 1.506000 1.60500 0.3458 0.300030 0.3590000 -0.0008520 1.477000 1.58100 0.3477 0.303030 0.3602000 -0.0008737 1.466000 1.57300 0.3483 0.316960 0.3671000 -0.0009272 1.412000 1.52500 0.3491 0.320000 0.3690000 -0.0009468 1.397000 1.51200 0.3487 0.333330 0.3742000 -0.0010100 1.352000 1.47200 0.3474 0.340020 0.3752000 -0.0010060 1.337000 1.46100 0.3469 0.344830 0.3760000 -0.0009698 1.326000 1.45200 0.3471 0.357140 0.3807000 -0.0009114 1.286000 1.41500 0.3481 0.359970 0.3822000 -0.0009039 1.275000 1.40500 0.3484 0.370370 0.3867000 -0.0008635 1.237000 1.37200 0.3492 0.379940 0.3909000 -0.0008074 1.199000 1.33900 0.3500 0.384620 0.3931000 -0.0007955 1.179000 1.32100 0.3507 0.400000 0.3997000 -0.0007078 1.119000 1.26700 0.3517 0.416670 0.4028000 -0.0006613 1.078000 1.23200 0.3512 0.419990 0.4034000 -0.0006513 1.070000 1.22600 0.3513 0.434780 0.4070000 -0.0006167 1.029000 1.19100 0.3521 0.439950 0.4089000 -0.0006118 1.011000 1.17400 0.3527 0.454550 0.4148000 -0.0005931 0.960100 1.12500 0.3547 0.459980 0.4165000 -0.0005816 0.944000 1.10900 0.3549 0.476190 0.4222000 -0.0005404 0.893100 1.05800 0.3555 0.480080 0.4239000 -0.0005484 0.879500 1.04500 0.3556 0.500000 0.4323000 -0.0005680 0.815000 0.97970 0.3555 0.520020 0.4372000 -0.0005396 0.764200 0.93240 0.3568 0.526320 0.4379000 -0.0005050 0.752200 0.92080 0.3570 0.539960 0.4394000 -0.0004330 0.727100 0.89590 0.3574 0.555560 0.4418000 -0.0003601 0.694100 0.86610 0.3587 0.559910 0.4425000 -0.0003380 0.684400 0.85710 0.3592 0.580050 0.4472000 -0.0002702 0.635700 0.81170 0.3610 0.588240 0.4492000 -0.0002522 0.615700 0.79260 0.3609 0.599880 0.4516000 -0.0002175 0.589500 0.76820 0.3603 0.619960 0.4559000 -0.0001953 0.547800 0.72820 0.3604 0.625000 0.4569000 -0.0001995 0.538300 0.71870 0.3609 0.640200 0.4596000 -0.0001666 0.510600 0.69100 0.3625 0.660070 0.4637000 -0.0001549 0.472500 0.65200 0.3647 0.666670 0.4655000 -0.0001550 0.457300 0.63630 0.3649 0.679810 0.4688000 -0.0001668 0.428400 0.60810 0.3655 0.699790 0.4732000 -0.0001700 0.385700 0.56760 0.3667 0.714290 0.4771000 -0.0002019 0.354800 0.53540 0.3680 0.750190 0.4847000 -0.0003009 0.287100 0.46810 0.3700 0.769230 0.4875000 -0.0003122 0.254500 0.43800 0.3703 0.800000 0.4940000 -0.0002568 0.190600 0.37820 0.3714 0.833330 0.5010000 -0.0001932 0.126400 0.31450 0.3746 0.850340 0.5040000 -0.0001433 0.096150 0.28420 0.3758 0.900090 0.5098000 3.28E-05 0.020060 0.21300 0.3747 0.909090 0.5104000 8.39E-05 0.008195 0.20220 0.3744 1.000000 0.5199000 0.0002516 -0.116200 0.08290 0.3737 1.100100 0.5273000 0.0003908 -0.212300 -0.02900 0.3794 1.111100 0.5278000 0.0004074 -0.220700 -0.03875 0.3804 1.200500 0.5361000 0.0004479 -0.313300 -0.13380 0.3838 1.250000 0.5409000 0.0004860 -0.367900 -0.18910 0.3877 1.300400 0.5444000 0.0005329 -0.411300 -0.23770 0.3920 1.400600 0.5481000 0.0007676 -0.487000 -0.31550 0.3935 1.428600 0.5494000 0.0008272 -0.509500 -0.33850 0.3941 1.499300 0.5527000 0.0009124 -0.560400 -0.39350 0.3932 1.600000 0.5557000 0.0009844 -0.618600 -0.45830 0.3919 1.666700 0.5580000 0.0010850 -0.656400 -0.50260 0.3919 1.798600 0.5620000 0.0012450 -0.725800 -0.58340 0.3942 2.000000 0.5622000 0.0013750 -0.796300 -0.66600 0.4030 2.197800 0.5617000 0.0016520 -0.865600 -0.73950 0.4055 2.398100 0.5641000 0.0018290 -0.940600 -0.81580 0.4093 2.500000 0.5654000 0.0019210 -0.978700 -0.85420 0.4110 2.597400 0.5677000 0.0020060 -1.019000 -0.89800 0.4130 2.801100 0.5666000 0.0022770 -1.071000 -0.94950 0.4202 3.003000 0.5683000 0.0024490 -1.130000 -1.01400 0.4255 3.205100 0.5686000 0.0025360 -1.179000 -1.06900 0.4301 3.333300 0.5705000 0.0025330 -1.220000 -1.11100 0.4329 3.401400 0.5715000 0.0025410 -1.243000 -1.13500 0.4340 3.597100 0.5727000 0.0025730 -1.300000 -1.19400 0.4359 3.802300 0.5712000 0.0026620 -1.350000 -1.24200 0.4365 4.000000 0.5722000 0.0027110 -1.417000 -1.30300 0.4344 4.504500 0.5856000 0.0024490 -1.662000 -1.52000 0.4278 5.000000 0.5990000 0.0021050 -1.886000 -1.72900 0.4233 5.494500 0.6106000 0.0019410 -2.072000 -1.90400 0.4260 5.988000 0.6160000 0.0018800 -2.201000 -2.02800 0.4284 6.993000 0.6175000 0.0017660 -2.373000 -2.19200 0.4299 8.000000 0.6145000 0.0017210 -2.491000 -2.30800 0.4284 9.009000 0.6122000 0.0016370 -2.592000 -2.40800 0.4236 10.00000 0.6086000 0.0015630 -2.668000 -2.48500 0.4183 """)
[docs]class BergeThierryEtAl2003SIGMA(BergeThierryEtAl2003Ms): """ Implements GMPE developed by Catherine Berge-Thierry, Fabrice Cotton, Oona Scoti, Daphne-Anne Griot-Pommera, and Yoshimitsu Fukushima and published as "New Empirical Response Spectral Attenuation Laws For Moderate European Earthquakes" (2003, Journal of Earthquake Engineering, 193-222) The class implements also adjustment of the sigma value as required by the SIGMA project to make standard deviations compatible with Mw (the GMPE was originally developed for Ms). Additional reference: Carbon, D. et al., 2012, Final preliminary Probabilistic Hazard map for France's southeast 1/4, Deliverable D4-18, p.31, SIGMA project. """
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): return super()._get_mean_and_stddevs( sites, rup, dists, imt, stddev_types, mag_conversion_sigma=0.2)
[docs]class BergeThierryEtAl2003MwW(BergeThierryEtAl2003Ms): """ Mw version of the Berge-Thierry et al. (2003) GMPE. For this conversion we use the Weatherill et al. (2016) conversion equation between Ms and Mw Bilinear magnitude conversion relation. """
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): newrup = copy.copy(rup) if rup.mag <= 6.064: newrup.mag = (rup.mag - 2.369) / 0.616 return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.147/0.616) else: newrup.mag = (rup.mag - 0.100) / 0.994 return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.174/0.994)
[docs]class BergeThierryEtAl2003MwL_MED(BergeThierryEtAl2003Ms): """ Mw version of the Berge-Thierry et al. (2003) GMPE. For this conversion we use the Lolli et al. (2014) conversion equation between Ms and Mw for the Euro-Mediterranean region. Exponential model: Mw = exp(a+b*Ms)+c with slope=b*exp(a+b*Ms) Parameters: (a,b,c) = (2.133,0.063,-6.205) """
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): newrup = copy.copy(rup) newrup.mag = (np.log(rup.mag+6.205)-2.133)/0.063 slope= 0.063*np.exp(2.133+0.063*newrup.mag) return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.1703/slope)
[docs]class BergeThierryEtAl2003MwL_ITA(BergeThierryEtAl2003Ms): """ Mw version of the Berge-Thierry et al. (2003) GMPE. For this conversion we use the Lolli et al. (2014) conversion equation between Ms and Mw for the ITA region. Exponential model: Mw = exp(a+b*Ms)+c with slope=b*exp(a+b*Ms) Parameters: (a,b,c) = (1.421,0.108,-1.863) """
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): newrup = copy.copy(rup) newrup.mag = (np.log(rup.mag+1.863)-1.421)/0.108 slope = 0.108*np.exp(1.421+0.108*newrup.mag) return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.1685/slope)
[docs]class BergeThierryEtAl2003MwL_GBL(BergeThierryEtAl2003Ms): """ Mw version of the Berge-Thierry et al. (2003) GMPE. For this conversion we use the Lolli et al. (2014) conversion equation between Ms and Mw for the GBL region (i.e. Global Scale). Exponential model: Mw = exp(a+b*Ms)+c with slope=b*exp(a+b*Ms) Parameters: for Ms<=5.5: (a,b,c) = (2.133,0.063,-6.205) for Ms>5.5: (a,b,c) = (-0.109,0.229,2.586) """
[docs] def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types): newrup = copy.copy(rup) if rup.mag < 5.75: newrup.mag = (np.log(rup.mag + 6.205) - 2.133) / 0.063 slope = 0.063 * np.exp(2.133 + 0.063 * newrup.mag) return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.1703/slope) else: newrup.mag = (np.log(rup.mag - 2.586) + 0.109) / 0.229 slope= 0.229*np.exp(-0.109+0.229*newrup.mag) return super()._get_mean_and_stddevs( sites, newrup, dists, imt, stddev_types, mag_conversion_sigma=0.1462/slope)