def main():
gmpe = ngaw2()
ipe = AllenEtAl2012()
event_ids = np.unique(SHAKE_DF['event_id'])
i = 0
event_id = event_ids[i]
idx = np.where(SHAKE_DF['event_id'] == event_id)[0]
rx = base.RuptureContext()
rx.mag = np.array(SHAKE_DF['magnitude'])[idx]
rx.ztor = np.array(SHAKE_DF['ztor'])[idx]
rx.rake = np.full_like(rx.mag)
rx.width =
rx.hypo_depth = np.array(SHAKE_DF['hypo_depth'])[idx]
sx = base.SitesContext()
sx.vs30 = np.array(SHAKE_DF['CA Vs30'])[idx]
dx = base.DistancesContext()
dx.rjb = np.array(SHAKE_DF['r_jb'])[idx]
dx.rrup = np.array(SHAKE_DF['r_rup'])[idx]
dx.rx = np.array(SHAKE_DF['r_x'])[idx]
dx.ry = np.array(SHAKE_DF['r_y'])[idx]
dx.ry0 = np.array(SHAKE_DF['r_y0'])[idx]
lmean, lsd = gmpe.get_mean_and_stddevs(
sx, rx, dx, imt=IMTS[j], stddev_types=STD)
def getRuptureContext(self, gmpelist):
"""
Return an Openquake
`RuptureContext <http://docs.openquake.org/oq-hazardlib/master/gsim/index.html#openquake.hazardlib.gsim.base.RuptureContext>`__
suitable for any GMPE (except for those requiring hypo_loc).
If Source does not contain a Fault, strike, dip, ztor, and width will be
filled with default values. Rake may not be known, or may be estimated
from a focal mechanism.
:param gmpelist:
Sequence of hazardlib GMPE objects.
:raises:
ShakeMapException when a GMPE requiring 'hypo_loc' is passed in.
:returns:
RuptureContext object with all known parameters filled in.
"""
# rupturecontext constructor inputs:
# 'mag', 'strike', 'dip', 'rake', 'ztor', 'hypo_lon', 'hypo_lat',
# 'hypo_depth', 'width', 'hypo_loc'
for gmpe in gmpelist:
reqset = gmpe.REQUIRES_RUPTURE_PARAMETERS
if 'hypo_loc' in reqset:
raise ShakeMapException(
'Rupture parameter "hypo_loc" is not supported!')
rup = base.RuptureContext()
rup.mag = self.getEventParam('mag')
if self._fault is not None:
rup.strike = self._fault.getStrike()
rup.dip = self._fault.getDip()
rup.ztor = self._fault.getTopOfRupture()
rup.width = self._fault.getWidth()
else:
rup.strike = DEFAULT_STRIKE
rup.dip = self.getEventParam('dip')
rup.ztor = DEFAULT_ZTOR
rup.width = DEFAULT_WIDTH
if 'rake' in self._event_dict:
rup.rake = self.getEventParam('rake')
elif 'mech' in self._event_dict:
mech = self._event_dict['mech']
rup.rake = RAKEDICT[mech]
else:
rup.rake = RAKEDICT['ALL']
rup.hypo_lat = self.getEventParam('lat')
rup.hypo_lon = self.getEventParam('lon')
rup.hypo_depth = self.getEventParam('depth')
return rup
def getRuptureContext(self, gmpelist):
"""
Returns an Openquake `RuptureContext <http://docs.openquake.org/oq-hazardlib/master/gsim/index.html#openquake.hazardlib.gsim.base.RuptureContext>`__.
Args:
gmpelist (list): List of hazardlib GMPE objects.
Returns:
RuptureContext object with all known parameters filled in.
""" # noqa
origin = self._origin
# rupturecontext constructor inputs:
# 'mag', 'strike', 'dip', 'rake', 'ztor', 'hypo_lon', 'hypo_lat',
# 'hypo_depth', 'width', 'hypo_loc'
rx = base.RuptureContext()
rx.mag = origin.mag
rx.strike = self.getStrike()
rx.dip = self.getDip()
rx.ztor = self.getDepthToTop()
rx.width = self.getWidth()
if hasattr(origin, 'rake'):
rx.rake = origin.rake
elif hasattr(origin, 'mech'):
mech = origin.mech
rx.rake = constants.RAKEDICT[mech]
else:
rx.rake = constants.RAKEDICT['ALL']
rx.hypo_lat = origin.lat
rx.hypo_lon = origin.lon
rx.hypo_depth = origin.depth
return rx
from openquake.hazardlib.gsim import base
import openquake.hazardlib.imt as imt
from openquake.hazardlib.const import StdDev
from shakelib.gmpe.nga_east import NGAEast
home_dir = os.path.dirname(os.path.abspath(__file__))
data_dir = os.path.join(home_dir, 'nga_east_data')
stddev_types = [StdDev.TOTAL]
gmpe = NGAEast()
dx = base.DistancesContext()
dx.rrup = np.logspace(-1, np.log10(2000), 100)
rx = base.RuptureContext()
sx = base.SitesContext()
IMTS = [imt.PGA(), imt.PGV(), imt.SA(0.3), imt.SA(1.0), imt.SA(3.0)]
MAGS = [3, 5, 6, 7]
VS30 = [180, 380, 760, 2000]
def update_results():
# To build the data for testing
result = {}
for i in IMTS:
ikey = i.__str__()
result[ikey] = {}
def gmpe_avg(ztest):
'''
transforms cybershake dips and Rx
Parameters
----------
ztest: 2d numpy array of 12 feature data
Returns
-------
model_avg: average of base model predictions in ln m/s2
'''
import numpy as np
import openquake
from openquake.hazardlib.gsim.abrahamson_2014 import AbrahamsonEtAl2014 #ASK
from openquake.hazardlib.gsim.campbell_bozorgnia_2014 import CampbellBozorgnia2014 #CB
from openquake.hazardlib.gsim.chiou_youngs_2014 import ChiouYoungs2014 #CY
from openquake.hazardlib.gsim.boore_2014 import BooreEtAl2014 #BSSA
import openquake.hazardlib.imt as imt
from openquake.hazardlib.const import StdDev
import openquake.hazardlib.gsim.base as base
stddev_types = [StdDev.TOTAL]
period = [10, 7.5, 5, 4, 3, 2, 1, 0.5, 0.2, 0.1]
gmpeBSSAdata = np.zeros((ztest.shape[0], len(period)))
gmpeASKdata = np.zeros((ztest.shape[0], len(period)))
gmpeCBdata = np.zeros((ztest.shape[0], len(period)))
gmpeCYdata = np.zeros((ztest.shape[0], len(period)))
gmpeBSSAstd = np.zeros((ztest.shape[0], len(period)))
gmpeASKstd = np.zeros((ztest.shape[0], len(period)))
gmpeCBstd = np.zeros((ztest.shape[0], len(period)))
gmpeCYstd = np.zeros((ztest.shape[0], len(period)))
gmpeASK = AbrahamsonEtAl2014()
gmpeCB = CampbellBozorgnia2014()
gmpeCY = ChiouYoungs2014()
gmpeBSSA = BooreEtAl2014()
for i in range(ztest.shape[0]):
dx = base.DistancesContext()
dx.rjb = np.array([ztest[i, 9]])
#dx.rjb = np.logspace(-1, 2, 10)
# Magnitude and rake
rx = base.RuptureContext()
rx.mag = np.array([ztest[i, 0]])
rx.rake = np.array([ztest[i, 5]])
rx.hypo_depth = np.array([ztest[i, 7]])
# Vs30
sx = base.SitesContext()
sx.vs30 = np.array([ztest[i, 2]])
sx.vs30measured = 0
dx.rrup = np.array([ztest[i, 1]])
rx.ztor = np.array([ztest[i, 11]])
rx.dip = np.array([ztest[i, 6]])
rx.width = np.array([ztest[i, 8]])
# dx.rx=np.array([rxkeep[i]])
dx.rx = np.array([ztest[i, 10]])
dx.ry0 = np.array([0])
sx.z1pt0 = np.array([ztest[i, 3]])
sx.z2pt5 = np.array([ztest[i, 4]])
# Evaluate GMPE
#Unit of measure for Z1.0 is [m] (ASK)
#for period1 in period:
for ii in range(len(period)):
sx.vs30measured = 0
period1 = period[ii]
gmpeBSSAdata[i, ii], g = gmpeBSSA.get_mean_and_stddevs(
sx, rx, dx, imt.SA(period1), stddev_types)
gmpeBSSAstd[i, ii] = g[0][0]
gmpeCBdata[i, ii], g = gmpeCB.get_mean_and_stddevs(
sx, rx, dx, imt.SA(period1), stddev_types)
gmpeCBstd[i, ii] = g[0][0]
gmpeCYdata[i, ii], g = gmpeCY.get_mean_and_stddevs(
sx, rx, dx, imt.SA(period1), stddev_types)
gmpeCYstd[i, ii] = g[0][0]
sx.vs30measured = [0]
gmpeASKdata[i, ii], g = gmpeASK.get_mean_and_stddevs(
sx, rx, dx, imt.SA(period1), stddev_types)
gmpeASKstd[i, ii] = g[0][0]
model_avg = np.log(9.81 * np.exp(
np.mean([gmpeBSSAdata, gmpeCBdata, gmpeCYdata, gmpeASKdata], axis=0)))
#outputs ln m/s2
return model_avg
