def export_agg_losses_ebr(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
loss_types = dstore.get_attr('composite_risk_model', 'loss_types')
name, ext = export.keyfunc(ekey)
agg_losses = dstore[name]
oq = dstore['oqparam']
dtlist = [('event_tag', (numpy.string_, 100)), ('year', U32)
] + oq.loss_dt_list()
elt_dt = numpy.dtype(dtlist)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
sm_ids = sorted(rlzs_assoc.rlzs_by_smodel)
writer = writers.CsvWriter(fmt=writers.FIVEDIGITS)
for sm_id in sm_ids:
rlzs = rlzs_assoc.rlzs_by_smodel[sm_id]
try:
events = dstore['events/sm-%04d' % sm_id]
except KeyError:
continue
if not len(events):
continue
for rlz in rlzs:
dest = dstore.build_fname('agg_losses', rlz, 'csv')
eids = set()
rlzname = 'rlz-%03d' % rlz.ordinal
if rlzname not in agg_losses:
continue
for loss_type in agg_losses[rlzname]:
dset = agg_losses['%s/%s' % (rlzname, loss_type)]
eids.update(dset['eid'])
eids = sorted(eids)
rlz_events = events[eids]
eid2idx = dict(zip(eids, range(len(eids))))
elt = numpy.zeros(len(eids), elt_dt)
elt['event_tag'] = build_etags(rlz_events)
elt['year'] = rlz_events['year']
for loss_type in loss_types:
elt_lt = elt[loss_type]
if oq.insured_losses:
elt_lt_ins = elt[loss_type + '_ins']
key = 'rlz-%03d/%s' % (rlz.ordinal, loss_type)
if key not in agg_losses: # nothing was saved for this key
continue
data = agg_losses[key].value
for i, eid in numpy.ndenumerate(data['eid']):
idx = eid2idx[eid]
if oq.insured_losses:
elt_lt[idx] = data['loss'][i, 0]
elt_lt_ins[idx] = data['loss'][i, 1]
else:
elt_lt[idx] = data['loss'][i]
elt.sort(order='event_tag')
writer.save(elt, dest)
return writer.getsaved()
def export_all_loss_ratios(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
loss_types = dstore.get_attr('composite_risk_model', 'loss_types')
name, ext = export.keyfunc(ekey)
ass_losses = dstore[name]
assetcol = dstore['assetcol']
oq = dstore['oqparam']
dtlist = [('event_tag', (numpy.string_, 100)), ('year', U32),
('aid', U32)] + oq.loss_dt_list()
elt_dt = numpy.dtype(dtlist)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
sm_id, eid = get_sm_id_eid(ekey[0])
if sm_id is None:
return []
sm_id, eid = int(sm_id), int(eid)
sm_ids = [sm_id]
zero = [0, 0] if oq.insured_losses else 0
writer = writers.CsvWriter(fmt=writers.FIVEDIGITS)
for sm_id in sm_ids:
rlzs = rlzs_assoc.rlzs_by_smodel[sm_id]
try:
event = dstore['events/sm-%04d' % sm_id][eid]
except KeyError:
continue
[event_tag] = build_etags([event])
for rlz in rlzs:
exportname = 'losses-sm=%04d-eid=%d' % (sm_id, eid)
dest = dstore.build_fname(exportname, rlz, 'csv')
losses_by_aid = AccumDict()
rlzname = 'rlz-%03d' % rlz.ordinal
for loss_type in ass_losses[rlzname]:
data = get_array(ass_losses['%s/%s' % (rlzname, loss_type)],
eid=eid)
losses_by_aid += group_by_aid(data, loss_type)
elt = numpy.zeros(len(losses_by_aid), elt_dt)
elt['event_tag'] = event_tag
elt['year'] = event['year']
elt['aid'] = sorted(losses_by_aid)
for i, aid in numpy.ndenumerate(elt['aid']):
for loss_type in loss_types:
value = assetcol[int(aid)].value(loss_type, oq.time_event)
loss = value * losses_by_aid[aid].get(loss_type, zero)
if oq.insured_losses:
elt[loss_type][i] = loss[0]
elt[loss_type + '_ins'][i] = loss[1]
else:
elt[loss_type][i] = loss
elt.sort(order='event_tag')
writer.save(elt, dest)
return writer.getsaved()
def export_agg_losses(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
agg_losses = dstore[ekey[0]].value
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
etags = build_etags(dstore['events'])
writer = writers.CsvWriter(fmt=writers.FIVEDIGITS)
for rlz in rlzs:
losses = agg_losses[:, rlz.ordinal]
dest = dstore.build_fname('agg_losses', rlz, 'csv')
data = compose_arrays(etags, losses)
writer.save(data, dest)
return writer.getsaved()
