def export_damages_csv(ekey, dstore):
oq = dstore['oqparam']
dmg_dt = build_damage_dt(dstore)
rlzs = dstore['full_lt'].get_realizations()
data = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
assets = get_assets(dstore)
md = dstore.metadata
if oq.investigation_time:
md.update(
dict(investigation_time=oq.investigation_time,
risk_investigation_time=oq.risk_investigation_time))
if ekey[0].endswith('stats'):
rlzs_or_stats = oq.hazard_stats()
else:
rlzs_or_stats = ['rlz-%03d' % r for r in range(len(rlzs))]
name = ekey[0].split('-')[0]
if oq.calculation_mode != 'classical_damage':
name = 'avg_' + name
for i, ros in enumerate(rlzs_or_stats):
if oq.modal_damage_state:
damages = modal_damage_array(data[:, i], dmg_dt)
else:
damages = build_damage_array(data[:, i], dmg_dt)
fname = dstore.build_fname(name, ros, ekey[1])
writer.save(compose_arrays(assets, damages),
fname,
comment=md,
renamedict=dict(id='asset_id'))
return writer.getsaved()
def export_dmg_by_asset_csv(ekey, dstore):
damage_dt = build_damage_dt(dstore)
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
data = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
assets = get_assets(dstore)
for rlz in rlzs:
dmg_by_asset = build_damage_array(data[:, rlz.ordinal], damage_dt)
fname = dstore.build_fname(ekey[0], rlz, ekey[1])
writer.save(compose_arrays(assets, dmg_by_asset), fname)
return writer.getsaved()
def export_dmg_by_tag_csv(ekey, dstore):
damage_dt = build_damage_dt(dstore)
tags = add_quotes(dstore['assetcol'].tagcol)
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
data = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
for rlz in rlzs:
dmg_by_tag = build_damage_array(data[:, rlz.ordinal], damage_dt)
fname = dstore.build_fname(ekey[0], rlz, ekey[1])
array = compose_arrays(tags, dmg_by_tag, 'tag')
writer.save(array, fname)
return writer.getsaved()
def export_dmg_totalcsv(ekey, dstore):
damage_dt = build_damage_dt(dstore)
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
dset = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
for rlz in rlzs:
dmg_total = build_damage_array(dset[rlz.ordinal], damage_dt)
fname = dstore.build_fname(ekey[0], rlz, ekey[1])
data = [['loss_type', 'damage_state', 'damage_value']]
for loss_type in dmg_total.dtype.names:
tot = dmg_total[loss_type]
for name in tot.dtype.names:
data.append((loss_type, name, tot[name]))
writer.save(data, fname)
return writer.getsaved()
def export_dmg_by_asset_csv(ekey, dstore):
E = len(dstore['events'])
oq = dstore['oqparam']
damage_dt = build_damage_dt(dstore, mean_std=E > 1)
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
data = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
assets = get_assets(dstore)
for rlz in rlzs:
if oq.modal_damage_state:
dmg_by_asset = modal_damage_array(data[:, rlz.ordinal], damage_dt)
else:
dmg_by_asset = build_damage_array(data[:, rlz.ordinal], damage_dt)
fname = dstore.build_fname(ekey[0], rlz, ekey[1])
writer.save(compose_arrays(assets, dmg_by_asset), fname)
return writer.getsaved()
def export_dmg_by_asset_csv(ekey, dstore):
E = len(dstore['events'])
oq = dstore['oqparam']
damage_dt = build_damage_dt(dstore, mean_std=E > 1)
rlzs = dstore['csm_info'].get_rlzs_assoc().realizations
data = dstore[ekey[0]]
writer = writers.CsvWriter(fmt='%.6E')
assets = get_assets(dstore)
for rlz in rlzs:
if oq.modal_damage_state:
dmg_by_asset = modal_damage_array(data[:, rlz.ordinal], damage_dt)
else:
dmg_by_asset = build_damage_array(data[:, rlz.ordinal], damage_dt)
fname = dstore.build_fname(ekey[0], rlz, ekey[1])
writer.save(compose_arrays(assets, dmg_by_asset), fname)
return writer.getsaved()
def export_damages_csv(ekey, dstore):
oq = dstore['oqparam']
ebd = oq.calculation_mode == 'event_based_damage'
dmg_dt = build_damage_dt(dstore)
rlzs = dstore['full_lt'].get_realizations()
orig = dstore[ekey[0]][:] # shape (A, R, L, D)
writer = writers.CsvWriter(fmt='%.6E')
assets = get_assets(dstore)
md = dstore.metadata
if oq.investigation_time:
rit = oq.risk_investigation_time or oq.investigation_time
md.update(
dict(investigation_time=oq.investigation_time,
risk_investigation_time=rit))
D = len(oq.limit_states) + 1
R = 1 if oq.collect_rlzs else len(rlzs)
if ekey[0].endswith('stats'):
rlzs_or_stats = oq.hazard_stats()
else:
rlzs_or_stats = ['rlz-%03d' % r for r in range(R)]
name = ekey[0].split('-')[0]
if oq.calculation_mode != 'classical_damage':
name = 'avg_' + name
for i, ros in enumerate(rlzs_or_stats):
if ebd: # export only the consequences from damages-rlzs, i == 0
rate = len(dstore['events']) * oq.time_ratio / len(rlzs)
data = orig[:, i] * rate
A, L, Dc = data.shape
if Dc == D: # no consequences, export nothing
return
csq_dt = build_csq_dt(dstore)
damages = numpy.zeros(A, csq_dt)
for a in range(A):
for li, lt in enumerate(csq_dt.names):
damages[lt][a] = tuple(data[a, li, D:Dc])
fname = dstore.build_fname('avg_risk', ros, ekey[1])
else: # scenario_damage, classical_damage
if oq.modal_damage_state:
damages = modal_damage_array(orig[:, i], dmg_dt)
else:
damages = build_damage_array(orig[:, i], dmg_dt)
fname = dstore.build_fname(name, ros, ekey[1])
writer.save(compose_arrays(assets, damages),
fname,
comment=md,
renamedict=dict(id='asset_id'))
return writer.getsaved()
