def get_loss_maps(dstore, kind):
"""
:param dstore: a DataStore instance
:param kind: 'rlzs' or 'stats'
"""
oq = dstore['oqparam']
name = 'rcurves-%s' % kind
if name in dstore: # event_based risk
values = dstore['assetcol'].values()
_, loss_maps_dt = scientific.build_loss_dtypes(
{lt: len(oq.loss_ratios[lt]) for lt in oq.loss_ratios},
oq.conditional_loss_poes, oq.insured_losses)
rcurves = dstore[name].value # to support Ubuntu 14
A, R, I = rcurves.shape
ins = ['', '_ins']
loss_maps = numpy.zeros((A, R), loss_maps_dt)
for ltype, lratios in oq.loss_ratios.items():
for (a, r, i) in indices(A, R, I):
rcurve = rcurves[ltype][a, r, i]
losses = numpy.array(lratios) * values[ltype][a]
tup = tuple(
scientific.conditional_loss_ratio(losses, rcurve, poe)
for poe in oq.conditional_loss_poes)
loss_maps[ltype + ins[i]][a, r] = tup
return loss_maps
name = 'loss_curves-%s' % kind
if name in dstore: # classical_risk
loss_curves = dstore[name]
loss_maps = scientific.broadcast(
scientific.loss_maps, loss_curves, oq.conditional_loss_poes)
return loss_maps
def get_loss_maps(dstore, kind):
"""
:param dstore: a DataStore instance
:param kind: 'rlzs' or 'stats'
"""
oq = dstore['oqparam']
name = 'loss_maps-%s' % kind
if name in dstore: # event_based risk
return dstore[name].value.view(oq.loss_maps_dt())
name = 'loss_curves-%s' % kind
if name in dstore: # classical_risk
loss_curves = dstore[name]
loss_maps = scientific.broadcast(scientific.loss_maps, loss_curves,
oq.conditional_loss_poes)
return loss_maps
raise KeyError('loss_maps/loss_curves missing in %s' % dstore)
def get_loss_maps(dstore, kind):
"""
:param dstore: a DataStore instance
:param kind: 'rlzs' or 'stats'
"""
oq = dstore['oqparam']
name = 'loss_maps-%s' % kind
if name in dstore: # event_based risk
return _to_loss_maps(dstore[name].value, oq.loss_maps_dt())
name = 'loss_curves-%s' % kind
if name in dstore: # classical_risk
# the loss maps are built on the fly from the loss curves
loss_curves = dstore[name]
loss_maps = scientific.broadcast(
scientific.loss_maps, loss_curves, oq.conditional_loss_poes)
return loss_maps
raise KeyError('loss_maps/loss_curves missing in %s' % dstore)
