def test_gm_calculation_soil_reference(self):
# Modified gmpe
mgmpe = CY14SiteTerm(gmpe_name='ChiouYoungs2014')
# Set parameters
sites = Dummy.get_site_collection(4,
vs30=1130.,
vs30measured=True,
z1pt0=0.)
rup = Dummy.get_rupture(mag=6.0)
rup.dip = 90.
rup.ztor = 0.
rup.rrup = np.array([1., 10., 30., 70.])
rup.rx = np.array([1., 10., 30., 70.])
rup.rjb = np.array([1., 10., 30., 70.])
ctx = full_context(sites, rup)
imt = PGA()
stdt = [StdDev.TOTAL]
# Compute results
mean, stds = mgmpe.get_mean_and_stddevs(ctx, ctx, ctx, imt, stdt)
# Compute the expected results
gmpe = ChiouYoungs2014()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(
ctx, ctx, ctx, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean, mean_expected)
np.testing.assert_almost_equal(stds, stds_expected)
def test_gm_calculation_soil_BC(self):
""" Test mean and std calculation - CY14 on BC soil"""
# Modified gmpe
mgmpe = CY14SiteTerm(gmpe_name='ChiouYoungs2014')
# Set parameters
sites = Dummy.get_site_collection(4,
vs30=760.,
vs30measured=True,
z1pt0=0.)
rup = Dummy.get_rupture(mag=6.0)
rup.dip = 90.
rup.ztor = 0.
dists = DistancesContext()
dists.rrup = np.array([1., 10., 30., 70.])
dists.rx = np.array([1., 10., 30., 70.])
dists.rjb = np.array([1., 10., 30., 70.])
imt = PGA()
stdt = [const.StdDev.TOTAL]
# Compute results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
# Compute the expected results
gmpe = ChiouYoungs2014()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(
sites, rup, dists, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean, mean_expected, decimal=7)
np.testing.assert_almost_equal(stds, stds_expected, decimal=2)
def test_gm_calculation_hard_rock(self):
""" Test mean and std calculation - on hard rock using AB06"""
# Modified gmpe
mgmpe = NRCan15SiteTermLinear(gmpe_name='AtkinsonBoore2006')
# Set parameters
sites = Dummy.get_site_collection(2, vs30=[760, 2010])
rup = Dummy.get_rupture(mag=7.0)
dists = DistancesContext()
dists.rrup = np.array([15., 15.])
stdt = [const.StdDev.TOTAL]
gmpe = AtkinsonBoore2006()
for imt in [PGA(), SA(1.0), SA(5.0)]:
#
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt,
stdt)
# Compute the expected results
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(
sites, rup, dists, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives
# the same results of the original gmpe
np.testing.assert_allclose(np.exp(mean),
np.exp(mean_expected),
rtol=1.0e-1)
np.testing.assert_allclose(stds, stds_expected)
def setUp(self):
fname = gettemp(ampl_func)
df = read_csv(fname, {
'ampcode': ampcode_dt,
None: numpy.float64
},
index='ampcode')
self.df = AmplFunction(df)
# Set GMMs
gmmA = BooreAtkinson2008()
# Set parameters
dsts = [10., 15., 20., 30., 40.]
dsts = [10.]
imts = [PGA(), SA(1.0)]
sites = Dummy.get_site_collection(len(dsts), vs30=760.0)
self.mag = 5.5
rup = Dummy.get_rupture(mag=self.mag)
ctx = full_context(sites, rup)
ctx.rjb = numpy.array(dsts)
ctx.rrup = numpy.array(dsts)
self.rrup = ctx.rrup
# Compute GM on rock
self.cmaker = ContextMaker('TRT', [gmmA],
dict(imtls={str(im): [0]
for im in imts}))
[self.meastd] = self.cmaker.get_mean_stds([ctx], const.StdDev.TOTAL)
def setUp(self):
fname = gettemp(ampl_func)
df = read_csv(fname, {
'ampcode': ampcode_dt,
None: numpy.float64
},
index='ampcode')
self.df = AmplFunction(df)
# Set GMMs
gmmA = BooreAtkinson2008()
gmmB = BooreEtAl2014()
# Set parameters
dsts = [10., 15., 20., 30., 40.]
dsts = [10.]
imts = [PGA(), SA(1.0)]
sites = Dummy.get_site_collection(len(dsts), vs30=760.0)
self.mag = 5.5
rup = Dummy.get_rupture(mag=self.mag)
ctx = RuptureContext.full(rup, sites)
ctx.rjb = numpy.array(dsts)
ctx.rrup = numpy.array(dsts)
self.rrup = ctx.rrup
# Compute GM on rock
self.meastd = gmmA.get_mean_std([ctx], imts) # shape (2, N=1, M=2)
def test_gm_calculation_hard_rock(self):
""" Test mean and std calculation - on hard rock using AB06"""
# Modified gmpe
mgmpe = NRCan15SiteTermLinear(gmpe_name='AtkinsonBoore2006')
# Set parameters
sites = Dummy.get_site_collection(2, vs30=[760, 2010])
rup = Dummy.get_rupture(mag=7.0)
dists = DistancesContext()
dists.rrup = np.array([15., 15.])
stdt = [const.StdDev.TOTAL]
gmpe = AtkinsonBoore2006()
for imt in [PGA(), SA(1.0), SA(5.0)]:
#
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt,
stdt)
# Compute the expected results
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(sites,
rup, dists, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives
# the same results of the original gmpe
np.testing.assert_allclose(np.exp(mean), np.exp(mean_expected),
rtol=1.0e-1)
np.testing.assert_allclose(stds, stds_expected)
def setUp(self):
# Set parameters
self.sites = Dummy.get_site_collection(4, vs30=760.)
self.rup = Dummy.get_rupture(mag=6.0)
self.dists = DistancesContext()
self.dists.rrup = np.array([1., 10., 30., 70.])
self.dists.rjb = np.array([1., 10., 30., 70.])
self.imt = PGA()
def ctx(self, nsites, vs30):
sites = Dummy.get_site_collection(nsites, vs30=vs30)
rup = Dummy.get_rupture(mag=6.0)
ctx = RuptureContext()
vars(ctx).update(vars(rup))
for name in sites.array.dtype.names:
setattr(ctx, name, sites[name])
return ctx
def setUp(self):
# Set parameters
self.sites = Dummy.get_site_collection(
4, amplfactor=[-1.0, 1.5, 0.00, -1.99])
self.rup = Dummy.get_rupture(mag=6.0, hypo_depth=10)
self.dists = DistancesContext()
self.dists.rhypo = np.array([1., 10., 30., 70.])
self.dists.repi = np.array([1., 10., 30., 70.])
self.imt = MMI()
def get_ctx(subset_df):
locs = []
rjb = []
for idx, row in subset_df.iterrows():
locs.append(Point(row.lon_sites, row.lat_sites))
rjb.append(row.dist_jb)
sites = Dummy.get_site_collection(len(rjb), vs30=800., location=locs)
rup = Dummy.get_rupture(mag=row.rup_mag,
hypo_lat=row.lat_epi,
hypo_lon=row.lon_epi)
rup.rjb = np.array(rjb)
return contexts.full_context(sites, rup)
def test01(self):
filename = os.path.join(DATA_PATH, 'kappa.txt')
gmm = AlAtikSigmaModel(gmpe_name='BindiEtAl2014Rjb',
kappa_file=filename,
kappa_val='high')
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rjb = np.array([1., 10., 30., 70.])
imt = SA(0.1)
stdt = [const.StdDev.TOTAL]
mean_expected, stds_expected = gmm.get_mean_and_stddevs(
sites, rup, dists, imt, stdt)
def setUp(self):
# Set parameters - Setting z1pt0 does not make sense but here we
# want to make sure that the modified gmm provided GM amplified
# by the site term exactly as the original model.
sites = Dummy.get_site_collection(4,
vs30=400.,
vs30measured=True,
z1pt0=0.)
rup = Dummy.get_rupture(mag=6.0)
rup.dip = 90.
rup.ztor = 0.
rup.rrup = np.array([1., 10., 30., 70.])
rup.rx = np.array([1., 10., 30., 70.])
rup.rjb = np.array([1., 10., 30., 70.])
stdt = [StdDev.TOTAL]
self.ctx = full_context(sites, rup)
self.stdt = stdt
self.sites = sites
def test02(self):
avg_periods = [0.05, 0.15, 1.0, 2.0, 4.0]
gmm = gsim.mgmpe.generic_gmpe_avgsa.GenericGmpeAvgSA(
gmpe_name='AkkarEtAlRepi2014',
avg_periods=avg_periods,
corr_func='akkar')
msg = 'The class name is incorrect'
self.assertTrue(gmm.__class__.__name__ == 'GenericGmpeAvgSA', msg=msg)
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.repi = np.array([1., 10., 30., 70.])
imtype = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, _ = gmm.get_mean_and_stddevs(sites, rup, dists, imtype, stdt)
expected = np.array([-2.0383581, -2.6548699, -3.767237, -4.7775653])
np.testing.assert_almost_equal(mean, expected)
def setUp(self):
self.ctx = ctx = RuptureContext()
ctx.mag = 6.0
ctx.hypo_depth = 10.
sites = Dummy.get_site_collection(4,
amplfactor=[-1.0, 1.5, 0.00, -1.99])
for name in sites.array.dtype.names:
setattr(ctx, name, sites[name])
ctx.rhypo = np.array([1., 10., 30., 70.])
ctx.repi = np.array([1., 10., 30., 70.])
self.imt = MMI()
def test02(self):
# checks if gmpe is always being evaluated at vs30=760
# see HID 2.6.2
filename = os.path.join(DATA_PATH, 'kappa.txt')
gmm = AlAtikSigmaModel(gmpe_name='YenierAtkinson2015ACME2019',
kappa_file=filename,
kappa_val='high')
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rjb = np.array([1., 10., 30., 70.])
dists.rrup = np.array([1., 10., 30., 70.])
imt = SA(0.1)
stdt = [const.StdDev.TOTAL]
mean_760, _ = gmm.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
sites2 = Dummy.get_site_collection(4, vs30=1500.)
mean_1500, _ = gmm.get_mean_and_stddevs(sites2, rup, dists, imt, stdt)
self.assertAlmostEqual(mean_760[-1], mean_1500[-1], 4)
def setUp(self):
self.ctx = ctx = RuptureContext()
ctx.mag = 6.
ctx.rake = 0.
ctx.hypo_depth = 10.
sites = Dummy.get_site_collection(4, vs30=760.)
for name in sites.array.dtype.names:
setattr(ctx, name, sites[name])
ctx.rrup = np.array([1., 10., 30., 70.])
ctx.rjb = np.array([1., 10., 30., 70.])
self.imt = PGA()
def test_gm_calculationAB06_hard_bedrock(self):
""" Test mean and std calculation - AB06 on vs30 hard bedrock"""
# Modified gmpe
mgmpe = NRCan15SiteTerm(gmpe_name='AtkinsonBoore2006')
# Set parameters
sites = Dummy.get_site_collection(4, vs30=1999.0)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rrup = np.array([10., 20., 30., 40.])
imt = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
# Compute the expected results
gmpe = AtkinsonBoore2006()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(
sites, rup, dists, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean, mean_expected)
np.testing.assert_almost_equal(stds, stds_expected)
def test_gm_calculationBA08_vs30variable(self):
""" Test mean and std calculation - BA08 - Vs30 variable"""
# Modified gmpe
mgmpe = NRCan15SiteTerm(gmpe_name='BooreAtkinson2008')
# Set parameters
sites = Dummy.get_site_collection(3, vs30=[400., 600, 1000])
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rjb = np.array([10., 10., 10.])
imt = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
# Compute the expected results
gmpe = BooreAtkinson2008()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(
sites, rup, dists, imt, stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean[:-1], mean_expected[:-1])
np.testing.assert_almost_equal(stds[:-1], stds_expected[:-1])
def _get_stds(self, within_absolute=None, between_absolute=None):
if within_absolute is not None:
gmm = SplitSigmaGMPE(gmpe_name='Campbell2003',
within_absolute=within_absolute)
elif between_absolute is not None:
gmm = SplitSigmaGMPE(gmpe_name='Campbell2003',
between_absolute=between_absolute)
else:
raise ValueError('Unknown option')
# Set parameters
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rrup = np.array([1., 10., 30., 70.])
imt = PGA()
stds_types = [const.StdDev.TOTAL, const.StdDev.INTER_EVENT,
const.StdDev.INTRA_EVENT]
# Compute results
mean, stds = gmm.get_mean_and_stddevs(sites, rup, dists, imt,
stds_types)
return stds, stds_types
def test01(self):
avg_periods = [0.05, 0.15, 1.0, 2.0, 4.0]
gmm = gsim.mgmpe.generic_gmpe_avgsa.GenericGmpeAvgSA(
gmpe_name='ZhaoEtAl2006Asc',
avg_periods=avg_periods,
corr_func='akkar')
msg = 'The class name is incorrect'
self.assertTrue(gmm.__class__.__name__ == 'GenericGmpeAvgSA', msg=msg)
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
rup.hypo_depth = 10.
dists = DistancesContext()
dists.rrup = np.array([1., 10., 30., 70.])
imtype = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, _ = gmm.get_mean_and_stddevs(sites, rup, dists, imtype, stdt)
expected = np.array(
[-1.33735637, -2.62649473, -3.64500654, -4.60067093])
np.testing.assert_almost_equal(mean, expected)
def test_gm_calculationBA08_vs30variable(self):
""" Test mean and std calculation - BA08 - Vs30 variable"""
# Modified gmpe
mgmpe = NRCan15SiteTerm(gmpe_name='BooreAtkinson2008')
# Set parameters
sites = Dummy.get_site_collection(3, vs30=[400., 600, 1000])
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rjb = np.array([10., 10., 10.])
imt = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
# Compute the expected results
gmpe = BooreAtkinson2008()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(sites, rup,
dists, imt,
stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean[:-1], mean_expected[:-1])
np.testing.assert_almost_equal(stds[:-1], stds_expected[:-1])
def test_gm_calculationAB06_hard_bedrock(self):
""" Test mean and std calculation - AB06 on vs30 hard bedrock"""
# Modified gmpe
mgmpe = NRCan15SiteTerm(gmpe_name='AtkinsonBoore2006')
# Set parameters
sites = Dummy.get_site_collection(4, vs30=1999.0)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rrup = np.array([10., 20., 30., 40.])
imt = PGA()
stdt = [const.StdDev.TOTAL]
# Computes results
mean, stds = mgmpe.get_mean_and_stddevs(sites, rup, dists, imt, stdt)
# Compute the expected results
gmpe = AtkinsonBoore2006()
mean_expected, stds_expected = gmpe.get_mean_and_stddevs(sites, rup,
dists, imt,
stdt)
# Test that for reference soil conditions the modified GMPE gives the
# same results of the original gmpe
np.testing.assert_almost_equal(mean, mean_expected)
np.testing.assert_almost_equal(stds, stds_expected)
def _get_stds(self, within_absolute=None, between_absolute=None):
if within_absolute is not None:
gmm = SplitSigmaGMPE(gmpe_name='Campbell2003',
within_absolute=within_absolute)
elif between_absolute is not None:
gmm = SplitSigmaGMPE(gmpe_name='Campbell2003',
between_absolute=between_absolute)
else:
raise ValueError('Unknown option')
# Set parameters
sites = Dummy.get_site_collection(4, vs30=760.)
rup = Dummy.get_rupture(mag=6.0)
dists = DistancesContext()
dists.rrup = np.array([1., 10., 30., 70.])
imt = PGA()
stds_types = [
const.StdDev.TOTAL, const.StdDev.INTER_EVENT,
const.StdDev.INTRA_EVENT
]
# Compute results
mean, stds = gmm.get_mean_and_stddevs(sites, rup, dists, imt,
stds_types)
return stds, stds_types
