def full_enum(self):
# compute the mean curve with full enumeration
srcs = []
weights = []
grp_id = 0
for weight, branches in self.bs0.enumerate_paths():
path = tuple(br.branch_id for br in branches)
bset_values = self.bs0.get_bset_values(path)
# first path: [(<b01 b02>, (4.6, 1.1)), (<b11 b12>, 7.0)]
sg = lt.apply_uncertainties(bset_values, self.sg)
for src in sg:
src.grp_id = grp_id
grp_id += 1
srcs.extend(sg)
weights.append(weight)
for i, src in enumerate(srcs):
src.id = i
res = classical(
srcs, self.srcfilter, self.gsims,
dict(imtls=self.imtls, truncation_level2=2, collapse_ctxs=True))
pmap = res['pmap']
effrups = sum(nr for nr, ns, dt in res['calc_times'].values())
curves = [pmap[grp_id].array[0, :, 0] for grp_id in sorted(pmap)]
mean = numpy.average(curves, axis=0, weights=weights)
return mean, srcs, effrups, weights
def full_enum(self):
# compute the mean curve with full enumeration
srcs = []
weights = []
grp_id = trt_smr = 0
for weight, branches in self.bs0.enumerate_paths():
path = tuple(br.branch_id for br in branches)
bset_values = self.bs0.get_bset_values(path)
# first path: [(<b01 b02>, (4.6, 1.1)), (<b11 b12>, 7.0)]
sg = lt.apply_uncertainties(bset_values, self.sg)
for src in sg:
src.grp_id = grp_id
src.trt_smr = trt_smr
grp_id += 1
trt_smr += 1
srcs.extend(sg)
weights.append(weight)
for i, src in enumerate(srcs):
src.id = i
N = len(self.sitecol.complete)
time_span = srcs[0].temporal_occurrence_model.time_span
idist = calc.filters.IntegrationDistance.new('200')
params = dict(imtls=self.imtls,
truncation_level2=2,
collapse_level=2,
investigation_time=time_span,
maximum_distance=idist('default'))
cmaker = contexts.ContextMaker(srcs[0].tectonic_region_type,
self.gsims, params)
res = classical(srcs, self.sitecol, cmaker)
pmap = res['pmap']
effrups = sum(nr for nr, ns, dt in res['calc_times'].values())
curve = pmap.array(N)[0, :, 0]
return curve, srcs, effrups, weights
def full_enum(self):
# compute the mean curve with full enumeration
srcs = []
weights = []
grp_id = et_id = 0
for weight, branches in self.bs0.enumerate_paths():
path = tuple(br.branch_id for br in branches)
bset_values = self.bs0.get_bset_values(path)
# first path: [(<b01 b02>, (4.6, 1.1)), (<b11 b12>, 7.0)]
sg = lt.apply_uncertainties(bset_values, self.sg)
for src in sg:
src.grp_id = grp_id
src.et_id = et_id
grp_id += 1
et_id += 1
srcs.extend(sg)
weights.append(weight)
for i, src in enumerate(srcs):
src.id = i
N = len(self.srcfilter.sitecol.complete)
res = classical(
srcs, self.srcfilter, self.gsims,
dict(imtls=self.imtls, truncation_level2=2, collapse_level=2))
pmap = res['pmap']
effrups = sum(nr for nr, ns, dt in res['calc_times'].values())
curve = pmap.array(N)[0, :, 0]
return curve, srcs, effrups, weights
def _build_groups(full_lt, smdict):
# build all the possible source groups from the full logic tree
smlt_file = full_lt.source_model_lt.filename
smlt_dir = os.path.dirname(smlt_file)
def _groups_ids(value):
# extract the source groups and ids from a sequence of source files
groups = []
for name in value.split():
fname = os.path.abspath(os.path.join(smlt_dir, name))
groups.extend(smdict[fname].src_groups)
return groups, set(src.source_id for grp in groups for src in grp)
groups = []
for rlz in full_lt.sm_rlzs:
src_groups, source_ids = _groups_ids(rlz.value)
bset_values = full_lt.source_model_lt.bset_values(rlz)
if bset_values and bset_values[0][0].uncertainty_type == 'extendModel':
(bset, value), *bset_values = bset_values
extra, extra_ids = _groups_ids(value)
common = source_ids & extra_ids
if common:
raise InvalidFile(
'%s contains source(s) %s already present in %s' %
(value, common, rlz.value))
src_groups.extend(extra)
for src_group in src_groups:
grp_id = full_lt.get_grp_id(src_group.trt, rlz.ordinal)
sg = apply_uncertainties(bset_values, src_group)
for src in sg:
src.grp_id = grp_id
if rlz.samples > 1:
src.samples = rlz.samples
groups.append(sg)
# check applyToSources
sm_branch = rlz.lt_path[0]
srcids = full_lt.source_model_lt.info.applytosources[sm_branch]
for srcid in srcids:
if srcid not in source_ids:
raise ValueError(
"The source %s is not in the source model,"
" please fix applyToSources in %s or the "
"source model(s) %s" % (srcid, smlt_file,
rlz.value.split()))
return groups
