def get_conditional_gmfs(database,
rupture,
sites,
gsims,
imts,
number_simulations,
truncation_level,
correlation_model=DEFAULT_CORRELATION):
"""
Get a set of random fields conditioned on a set of observations
:param database:
Ground motion records for the event as instance of :class:
smtk.sm_database.GroundMotionDatabase
:param rupture:
Event rupture as instance of :class:
openquake.hazardlib.source.rupture.Rupture
:param sites:
Target sites as instance of :class:
openquake.hazardlib.site.SiteCollection
:param list gsims:
List of GMPEs required
:param list imts:
List of intensity measures required
:param int number_simulations:
Number of simulated fields required
:param float truncation_level:
Ground motion truncation level
"""
# Get known sites mesh
known_sites = database.get_site_collection()
# Get Observed Residuals
residuals = Residuals(gsims, imts)
residuals.get_residuals(database)
imt_dict = OrderedDict([(imtx,
np.zeros([len(sites.lons), number_simulations]))
for imtx in imts])
gmfs = OrderedDict([(gmpe, imt_dict) for gmpe in gsims])
gmpe_list = [GSIM_LIST[gmpe]() for gmpe in gsims]
cmaker = ContextMaker(rupture.tectonic_region_type, gmpe_list,
dict(imtls={imt: [0]
for imt in imts}))
ctxs = cmaker.get_ctxs([rupture], sites)
if len(ctxs) == 1: # engine version >= 3.13
rupture = sctx = dctx = ctxs[0]
else: # older versions
_rctx, sctx, dctx = ctxs
for gsim in gmpe_list:
gmpe = gsim.__class__.__name__
for imtx in imts:
if truncation_level == 0:
gmfs[gmpe][imtx], _ = gsim.get_mean_and_stddevs(
sctx, rupture, dctx, from_string(imtx), stddev_types=[])
continue
if "Intra event" in gsim.DEFINED_FOR_STANDARD_DEVIATION_TYPES:
epsilon = conditional_simulation(
known_sites,
residuals.residuals[gmpe][imtx]["Intra event"], sites,
imtx, number_simulations, correlation_model)
tau = np.unique(residuals.residuals[gmpe][imtx]["Inter event"])
mean, [stddev_inter, stddev_intra] = gsim.get_mean_and_stddevs(
sctx, rupture, dctx, from_string(imtx),
["Inter event", "Intra event"])
for iloc in range(0, number_simulations):
gmfs[gmpe][imtx][:, iloc] = np.exp(mean +
(tau * stddev_inter) +
(epsilon[:, iloc] *
stddev_intra))
else:
epsilon = conditional_simulation(
known_sites, residuals.residuals[gmpe][imtx]["Total"],
sites, imtx, number_simulations, correlation_model)
tau = None
mean, [stddev_total
] = gsim.get_mean_and_stddevs(sctx, rupture, dctx,
from_string(imtx),
["Total"])
for iloc in range(0, number_simulations):
gmfs[gmpe][imtx][:,
iloc] = np.exp(mean + epsilon[:, iloc] *
stddev_total.flatten())
return gmfs
