def compute_losses(ssm, sitecol, assetcol, riskmodel,
imts, trunc_level, correl_model, min_iml, monitor):
"""
Compute the losses for a single source model.
:param ssm: CompositeSourceModel containing a single source model
:param sitecol: a SiteCollection instance
:param assetcol: an AssetCollection instance
:param riskmodel: a RiskModel instance
:param imts: a list of Intensity Measure Types
:param trunc_level: truncation level
:param correl_model: correlation model
:param min_iml: vector of minimum intensities, one per IMT
:param monitor: a Monitor instance
:returns: a List containing the losses by taxonomy and some attributes
"""
[grp] = ssm.src_groups
res = List()
gsims = ssm.gsim_lt.values[DEFAULT_TRT]
res.ruptures_by_grp = compute_ruptures(grp, sitecol, gsims, monitor)
[(grp_id, ebruptures)] = res.ruptures_by_grp.items()
rlzs_assoc = ssm.info.get_rlzs_assoc()
num_rlzs = len(rlzs_assoc.realizations)
ri = riskinput.RiskInputFromRuptures(
DEFAULT_TRT, rlzs_assoc, imts, sitecol, ebruptures, trunc_level,
correl_model, min_iml)
res.append(event_based_risk(ri, riskmodel, assetcol, monitor))
res.sm_id = ssm.sm_id
res.num_events = len(ri.eids)
start = res.sm_id * num_rlzs
res.rlz_slice = slice(start, start + num_rlzs)
# don't return back the ruptures, only the events and rup_data
res.ruptures_by_grp[grp_id] = [EBR(ebr.serial, ebr.source_id, ebr.events)
for ebr in ebruptures]
return res
def compute_losses(ssm, src_filter, param, riskmodel,
imts, trunc_level, correl_model, min_iml, monitor):
"""
Compute the losses for a single source model. Returns the ruptures
as an attribute `.ruptures_by_grp` of the list of losses.
:param ssm: CompositeSourceModel containing a single source model
:param sitecol: a SiteCollection instance
:param param: a dictionary of parameters
:param riskmodel: a RiskModel instance
:param imts: a list of Intensity Measure Types
:param trunc_level: truncation level
:param correl_model: correlation model
:param min_iml: vector of minimum intensities, one per IMT
:param monitor: a Monitor instance
:returns: a List containing the losses by taxonomy and some attributes
"""
[grp] = ssm.src_groups
res = List()
gsims = ssm.gsim_lt.values[DEFAULT_TRT]
ruptures_by_grp = compute_ruptures(
grp, src_filter, gsims, param, monitor)
[(grp_id, ebruptures)] = ruptures_by_grp.items()
rlzs_assoc = ssm.info.get_rlzs_assoc()
samples = ssm.info.get_samples_by_grp()
num_rlzs = len(rlzs_assoc.realizations)
rlzs_by_gsim = rlzs_assoc.get_rlzs_by_gsim(DEFAULT_TRT)
getter = getters.GmfGetter(
rlzs_by_gsim, ebruptures, src_filter.sitecol, imts, min_iml,
src_filter.integration_distance, trunc_level, correl_model,
samples[grp_id])
ri = riskinput.RiskInput(getter, param['assetcol'].assets_by_site())
res.append(event_based_risk(ri, riskmodel, param, monitor))
res.sm_id = ssm.sm_id
res.num_events = len(ri.hazard_getter.eids)
start = res.sm_id * num_rlzs
res.rlz_slice = slice(start, start + num_rlzs)
res.events_by_grp = ruptures_by_grp.events_by_grp
res.eff_ruptures = ruptures_by_grp.eff_ruptures
return res
