def compute_loss_ratio_curve(
self, col, row, asset, gmf_slice, loss_ratios):
"""Compute the loss ratio curve for a single asset."""
calc_proxy = self.calc_proxy
vuln_function = self.vuln_curves.get(
asset["taxonomy"], None)
if not vuln_function:
LOGGER.error(
"Unknown vulnerability function %s for asset %s"
% (asset["taxonomy"], asset["assetID"]))
return None
epsilon_provider = general.EpsilonProvider(calc_proxy.params)
loss_histogram_bins = calc_proxy.oq_job_profile.loss_histogram_bins
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function, gmf_slice, epsilon_provider, asset,
loss_histogram_bins, loss_ratios=loss_ratios)
# NOTE (jmc): Early exit if the loss ratio is all zeros
if not False in (loss_ratio_curve.ordinates == 0.0):
return None
key = kvs.tokens.loss_ratio_key(
self.calc_proxy.job_id, row, col, asset["assetID"])
kvs.get_client().set(key, loss_ratio_curve.to_json())
LOGGER.debug("Loss ratio curve is %s, write to key %s" %
(loss_ratio_curve, key))
return loss_ratio_curve
def _compute_loss_ratio_curve(self, asset, gmf, loss_ratios):
"""
Generates a loss ratio curve for the given asset.
"""
vulnerability_function = self.vulnerability_curves.get(
asset.taxonomy, None)
if not vulnerability_function:
LOGGER.error("Unknown vulnerability function %s for asset %s" %
(asset.taxonomy, asset.asset_ref))
return None
epsilon_provider = general.EpsilonProvider(self.job_ctxt.params)
loss_histogram_bins = self.job_ctxt.oq_job_profile.loss_histogram_bins
loss_ratio_curve = general.compute_loss_ratio_curve(
vulnerability_function,
gmf,
epsilon_provider,
asset,
loss_histogram_bins,
loss_ratios=loss_ratios)
return loss_ratio_curve
def get_loss_curve(point, vuln_function, asset):
"Compute loss curve basing on GMF data"
gmf_slice = gmf_slices[point.site]
loss_ratios = general.compute_loss_ratios(
vuln_function, gmf_slice, epsilon_provider, asset)
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function, gmf_slice, epsilon_provider, asset,
self.calc_proxy.oq_job_profile.loss_histogram_bins,
loss_ratios=loss_ratios)
return loss_ratio_curve.rescale_abscissae(asset["assetValue"])
def get_loss_curve(point, vuln_function, asset):
"Compute loss curve basing on GMF data"
gmf_slice = gmf_slices[point.site]
loss_ratios = general.compute_loss_ratios(
vuln_function, gmf_slice, epsilon_provider, asset)
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function, gmf_slice, epsilon_provider, asset,
self.job_ctxt.oq_job_profile.loss_histogram_bins,
loss_ratios=loss_ratios)
aggregate_curve.append(loss_ratios * asset.value)
return loss_ratio_curve.rescale_abscissae(asset.value)
def get_loss_curve(point, vuln_function, asset):
"Compute loss curve basing on GMF data"
gmf_slice = gmf_slices[point.site]
loss_ratios = general.compute_loss_ratios(vuln_function, gmf_slice,
epsilon_provider, asset)
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function,
gmf_slice,
epsilon_provider,
asset,
self.job_ctxt.oq_job_profile.loss_histogram_bins,
loss_ratios=loss_ratios)
aggregate_curve.append(loss_ratios * asset.value)
return loss_ratio_curve.rescale_abscissae(asset.value)
def get_loss_curve(site, vuln_function, asset):
"Compute loss curve basing on GMF data"
gmvs = self._get_gmvs_at(general.hazard_input_site(
self.job_ctxt, site))
gmf_slice = {"IMLs": gmvs, "TSES": self._tses(),
"TimeSpan": self._time_span()}
loss_ratios = general.compute_loss_ratios(
vuln_function, gmf_slice, epsilon_provider, asset)
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function, gmf_slice, epsilon_provider, asset,
self.job_ctxt.oq_job_profile.loss_histogram_bins,
loss_ratios=loss_ratios)
aggregate_curve.append(loss_ratios * asset.value)
return loss_ratio_curve.rescale_abscissae(asset.value)
def compute_loss_ratio_curve(self, col, row, asset, gmf_slice,
loss_ratios):
"""Compute the loss ratio curve for a single asset.
:param asset: the asset used to compute loss
:type asset: an :py:class:`openquake.db.model.ExposureData` instance
"""
job_ctxt = self.job_ctxt
vuln_function = self.vuln_curves.get(asset.taxonomy, None)
if not vuln_function:
LOGGER.error("Unknown vulnerability function %s for asset %s" %
(asset.taxonomy, asset.asset_ref))
return None
epsilon_provider = general.EpsilonProvider(job_ctxt.params)
loss_histogram_bins = job_ctxt.oq_job_profile.loss_histogram_bins
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function,
gmf_slice,
epsilon_provider,
asset,
loss_histogram_bins,
loss_ratios=loss_ratios)
# NOTE (jmc): Early exit if the loss ratio is all zeros
if not False in (loss_ratio_curve.ordinates == 0.0):
return None
key = kvs.tokens.loss_ratio_key(self.job_ctxt.job_id, row, col,
asset.asset_ref)
kvs.get_client().set(key, loss_ratio_curve.to_json())
LOGGER.debug("Loss ratio curve is %s, write to key %s" %
(loss_ratio_curve, key))
return loss_ratio_curve
def _compute_loss_ratio_curve(self, asset, gmf, loss_ratios):
"""
Generates a loss ratio curve for the given asset.
"""
vulnerability_function = self.vulnerability_curves.get(
asset.taxonomy, None)
if not vulnerability_function:
LOGGER.error("Unknown vulnerability function %s for asset %s"
% (asset.taxonomy, asset.asset_ref))
return None
epsilon_provider = general.EpsilonProvider(self.job_ctxt.params)
loss_histogram_bins = self.job_ctxt.oq_job_profile.loss_histogram_bins
loss_ratio_curve = general.compute_loss_ratio_curve(
vulnerability_function, gmf, epsilon_provider, asset,
loss_histogram_bins, loss_ratios=loss_ratios)
return loss_ratio_curve
def compute_loss_ratio_curve(self, col, row, asset, gmf_slice,
loss_ratios):
"""Compute the loss ratio curve for a single asset.
:param asset: the asset used to compute loss
:type asset: an :py:class:`openquake.db.model.ExposureData` instance
"""
job_ctxt = self.job_ctxt
vuln_function = self.vuln_curves.get(asset.taxonomy, None)
if not vuln_function:
LOGGER.error("Unknown vulnerability function %s for asset %s"
% (asset.taxonomy, asset.asset_ref))
return None
epsilon_provider = general.EpsilonProvider(job_ctxt.params)
loss_histogram_bins = job_ctxt.oq_job_profile.loss_histogram_bins
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function, gmf_slice, epsilon_provider, asset,
loss_histogram_bins, loss_ratios=loss_ratios)
# NOTE (jmc): Early exit if the loss ratio is all zeros
if not False in (loss_ratio_curve.ordinates == 0.0):
return None
key = kvs.tokens.loss_ratio_key(
self.job_ctxt.job_id, row, col, asset.asset_ref)
kvs.get_client().set(key, loss_ratio_curve.to_json())
LOGGER.debug("Loss ratio curve is %s, write to key %s" %
(loss_ratio_curve, key))
return loss_ratio_curve
def get_loss_curve(site, vuln_function, asset):
"Compute loss curve basing on GMF data"
gmvs = self._get_gmvs_at(
general.hazard_input_site(self.job_ctxt, site))
gmf_slice = {
"IMLs": gmvs,
"TSES": self._tses(),
"TimeSpan": self._time_span()
}
loss_ratios = general.compute_loss_ratios(vuln_function, gmf_slice,
epsilon_provider, asset)
loss_ratio_curve = general.compute_loss_ratio_curve(
vuln_function,
gmf_slice,
epsilon_provider,
asset,
self.job_ctxt.oq_job_profile.loss_histogram_bins,
loss_ratios=loss_ratios)
aggregate_curve.append(loss_ratios * asset.value)
return loss_ratio_curve.rescale_abscissae(asset.value)