def test_calculation_Baker_Jayaram(self):
DATA_FILE = data / 'GENERIC_GMPE_AVGSA_MEAN_STD_TOTAL_BAKER_JAYARAM.csv'
# Initialise meta-GMPE
mgmpe = gsim.mgmpe.generic_gmpe_avgsa.GenericGmpeAvgSA(
gmpe_name='BooreAtkinson2008',
avg_periods=[0.05, 0.15, 1.0, 2.0, 4.0],
corr_func='baker_jayaram')
ctx = RuptureContext()
ctx.sids = [0]
P = imt.AvgSA
S = [const.StdDev.TOTAL]
with open(DATA_FILE, 'r') as f:
# Skip header
for i in [1, 2, 3]:
f.readline()
for line in f:
arr = np.float_(line.strip().split(','))
# Setting ground motion attributes
ctx.mag = arr[0]
ctx.rjb = np.array([arr[1]])
ctx.rake = arr[2]
ctx.hypo_depth = arr[3]
ctx.vs30 = np.array([arr[4]])
# Compute ground motion
mean, stdv = mgmpe.get_mean_and_stddevs(ctx, ctx, ctx, P, S)
np.testing.assert_almost_equal(mean, arr[6])
np.testing.assert_almost_equal(stdv, arr[7])
def _prepare_ctxs(rupdata, cmaker, sitecol):
ctxs = []
for u in range(len(rupdata['mag'])):
ctx = RuptureContext()
for par in rupdata:
if not par.endswith('_'):
setattr(ctx, par, rupdata[par][u])
else: # site-dependent parameter
setattr(ctx, par[:-1], rupdata[par][u])
for par in cmaker.REQUIRES_SITES_PARAMETERS:
setattr(ctx, par, sitecol[par])
ctx.sids = sitecol.sids
ctxs.append(ctx)
return ctxs
def test_make_pmap(self):
trunclevel = 3
imtls = DictArray({'PGA': [0.01]})
gsims = [valid.gsim('AkkarBommer2010')]
ctxs = []
for occ_rate in (.001, .002):
ctx = RuptureContext()
ctx.mag = 5.5
ctx.rake = 90
ctx.occurrence_rate = occ_rate
ctx.sids = numpy.array([0.])
ctx.vs30 = numpy.array([760.])
ctx.rrup = numpy.array([100.])
ctx.rjb = numpy.array([99.])
ctxs.append(ctx)
pmap = make_pmap(ctxs, gsims, imtls, trunclevel, 50.)
numpy.testing.assert_almost_equal(pmap[0].array, 0.066381)
def test_get_pmap(self):
truncation_level = 3
imtls = DictArray({'PGA': [0.01]})
gsims = [valid.gsim('AkkarBommer2010')]
ctxs = []
for occ_rate in (.001, .002):
ctx = RuptureContext()
ctx.mag = 5.5
ctx.rake = 90
ctx.occurrence_rate = occ_rate
ctx.sids = numpy.array([0.])
ctx.vs30 = numpy.array([760.])
ctx.rrup = numpy.array([100.])
ctx.rjb = numpy.array([99.])
ctxs.append(ctx)
cmaker = ContextMaker(
'TRT', gsims, dict(imtls=imtls, truncation_level=truncation_level))
cmaker.tom = PoissonTOM(time_span=50)
pmap = cmaker.get_pmap(ctxs)
numpy.testing.assert_almost_equal(pmap[0].array, 0.066381)
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
ctx = RuptureContext()
ctx.mag = 6.0
ctx.sids = [0, 1, 2, 3]
ctx.vs30 = [760.] * 4
ctx.rrup = np.array([1., 10., 30., 70.])
ctx.occurrence_rate = .0001
imt = PGA()
stds_types = [const.StdDev.TOTAL, const.StdDev.INTER_EVENT,
const.StdDev.INTRA_EVENT]
# Compute results
mean, stds = gmm.get_mean_and_stddevs(ctx, ctx, ctx, imt, stds_types)
return stds, stds_types