Source code for openquake.calculators.classical_damage

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2014-2022 GEM Foundation
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <>.

import logging
import numpy
from openquake.baselib.general import AccumDict
from openquake.hazardlib import stats
from openquake.calculators import base, classical_risk, views

F32 = numpy.float32

[docs]def classical_damage(riskinputs, param, monitor): """ Core function for a classical damage computation. :param riskinputs: :class:`openquake.risklib.riskinput.RiskInput` objects :param param: dictionary of extra parameters :param monitor: :class:`openquake.baselib.performance.Monitor` instance :yields: dictionaries asset_ordinal -> damage(R, L, D) """ crmodel ='crmodel') mon = monitor('getting hazard', measuremem=False) for ri in riskinputs: R = ri.hazard_getter.num_rlzs L = len(crmodel.lti) D = len(crmodel.damage_states) result = AccumDict(accum=numpy.zeros((R, L, D), F32)) with mon: haz = ri.hazard_getter.get_hazard() for taxo, assets in ri.asset_df.groupby('taxonomy'): for rlz in range(R): pcurve = haz.extract(rlz) out = crmodel.get_output(taxo, assets, pcurve, rlz=rlz) for li, loss_type in enumerate(crmodel.loss_types): for a, frac in zip(assets.ordinal, out[loss_type]): result[a][rlz, li] = frac yield result
[docs]@base.calculators.add('classical_damage') class ClassicalDamageCalculator(classical_risk.ClassicalRiskCalculator): """ Scenario damage calculator """ core_task = classical_damage accept_precalc = ['classical']
[docs] def post_execute(self, result): """ Export the result in CSV format. :param result: a dictionary asset_ordinal -> array(R, L, D) """ D = len(self.crmodel.damage_states) damages = numpy.zeros((self.A, self.R, self.L, D), numpy.float32) for a in result: damages[a] = result[a] self.datastore['damages-rlzs'] = damages stats.set_rlzs_stats(self.datastore, 'damages', assets=self.assetcol['id'], loss_type=self.oqparam.loss_types, dmg_state=self.crmodel.damage_states) dmg = views.view('portfolio_damage', self.datastore)'\n' + views.text_table(dmg, ext='org'))