def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
if 'hazard_curves' in self.oqparam.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(self.oqparam)
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.sitecol, self.assets_by_site = self.assoc_assets_sites(
haz_sitecol)
curves_by_trt_gsim = {(0, 'FromFile'): haz_curves}
self.rlzs_assoc = logictree.trivial_rlzs_assoc()
self.save_mesh()
else: # compute hazard
super(ClassicalRiskCalculator, self).pre_execute()
logging.info('Preparing the risk input')
curves_by_trt_gsim = {}
for dset in self.datastore['curves_by_sm'].values():
for key, curves in dset.items():
trt_id, gsim = key.split('-')
curves_by_trt_gsim[int(trt_id), gsim] = curves.value
self.assetcol = riskinput.build_asset_collection(
self.assets_by_site, self.oqparam.time_event)
self.riskinputs = self.build_riskinputs(curves_by_trt_gsim)
self.monitor.oqparam = self.oqparam
self.N = sum(len(assets) for assets in self.assets_by_site)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = self.oqparam.insured_losses
self.Q1 = len(self.oqparam.quantile_loss_curves) + 1
def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
if 'hazard_curves' in self.oqparam.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(self.oqparam)
self.save_params()
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.assetcol = riskinput.AssetCollection(
self.assets_by_site, self.cost_calculator,
self.oqparam.time_event)
self.sitecol, self.assets_by_site = self.assoc_assets_sites(
haz_sitecol)
curves_by_trt_gsim = {(0, 'FromFile'): haz_curves}
self.rlzs_assoc = logictree.trivial_rlzs_assoc()
self.save_mesh()
else: # compute hazard or read it from the datastore
super(ClassicalRiskCalculator, self).pre_execute()
logging.info('Preparing the risk input')
curves_by_trt_gsim = {}
for dset in self.datastore['curves_by_sm'].values():
for key, curves in dset.items():
trt_id, gsim = key.split('-')
curves_by_trt_gsim[int(trt_id), gsim] = curves.value
self.riskinputs = self.build_riskinputs(curves_by_trt_gsim)
self.monitor.oqparam = self.oqparam
self.N = sum(len(assets) for assets in self.assets_by_site)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = self.oqparam.insured_losses
self.Q1 = len(self.oqparam.quantile_loss_curves) + 1
def test(self):
fname = general.writetmp('''\
<?xml version="1.0" encoding="utf-8"?>
<nrml xmlns:gml="http://www.opengis.net/gml"
xmlns="http://openquake.org/xmlns/nrml/0.4">
<!-- Spectral Acceleration (SA) example -->
<hazardCurves sourceModelTreePath="b1_b2_b4" gsimTreePath="b1_b2" investigationTime="50.0" IMT="SA" saPeriod="0.025" saDamping="5.0">
<IMLs>5.0000e-03 7.0000e-03 1.3700e-02</IMLs>
<hazardCurve>
<gml:Point>
<gml:pos>-122.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-01 9.8266e-01 9.4957e-01</poEs>
</hazardCurve>
<hazardCurve>
<gml:Point>
<gml:pos>-123.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8727e-02 9.8265e-02 9.4956e-02</poEs>
</hazardCurve>
</hazardCurves>
<!-- Basic example, using PGA as IMT -->
<hazardCurves sourceModelTreePath="b1_b2_b3" gsimTreePath="b1_b7" investigationTime="50.0" IMT="PGA">
<IMLs>5.0000e-03 7.0000e-03 1.3700e-02 3.3700e-02</IMLs>
<hazardCurve>
<gml:Point>
<gml:pos>-122.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-01 9.8226e-01 9.4947e-01 9.2947e-01</poEs>
</hazardCurve>
<hazardCurve>
<gml:Point>
<gml:pos>-123.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-02 9.8216e-02 9.4945e-02 9.2947e-02</poEs>
</hazardCurve>
</hazardCurves>
</nrml>
''',
suffix='.xml')
oqparam = mock.Mock()
oqparam.inputs = dict(hazard_curves=fname)
sitecol, hcurves = readinput.get_hcurves(oqparam)
self.assertEqual(len(sitecol), 2)
self.assertEqual(sorted(oqparam.hazard_imtls.items()),
[('PGA', [0.005, 0.007, 0.0137, 0.0337]),
('SA(0.025)', [0.005, 0.007, 0.0137])])
self.assertEqual(
str(hcurves), '''\
[([0.098727, 0.098265, 0.094956], [0.098728, 0.098216, 0.094945, 0.092947])
([0.98728, 0.98266, 0.94957], [0.98728, 0.98226, 0.94947, 0.92947])]''')
def test(self):
fname = general.writetmp('''\
<?xml version="1.0" encoding="utf-8"?>
<nrml xmlns:gml="http://www.opengis.net/gml"
xmlns="http://openquake.org/xmlns/nrml/0.4">
<!-- Spectral Acceleration (SA) example -->
<hazardCurves sourceModelTreePath="b1_b2_b4" gsimTreePath="b1_b2" investigationTime="50.0" IMT="SA" saPeriod="0.025" saDamping="5.0">
<IMLs>5.0000e-03 7.0000e-03 1.3700e-02</IMLs>
<hazardCurve>
<gml:Point>
<gml:pos>-122.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-01 9.8266e-01 9.4957e-01</poEs>
</hazardCurve>
<hazardCurve>
<gml:Point>
<gml:pos>-123.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8727e-02 9.8265e-02 9.4956e-02</poEs>
</hazardCurve>
</hazardCurves>
<!-- Basic example, using PGA as IMT -->
<hazardCurves sourceModelTreePath="b1_b2_b3" gsimTreePath="b1_b7" investigationTime="50.0" IMT="PGA">
<IMLs>5.0000e-03 7.0000e-03 1.3700e-02 3.3700e-02</IMLs>
<hazardCurve>
<gml:Point>
<gml:pos>-122.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-01 9.8226e-01 9.4947e-01 9.2947e-01</poEs>
</hazardCurve>
<hazardCurve>
<gml:Point>
<gml:pos>-123.5000 37.5000</gml:pos>
</gml:Point>
<poEs>9.8728e-02 9.8216e-02 9.4945e-02 9.2947e-02</poEs>
</hazardCurve>
</hazardCurves>
</nrml>
''', suffix='.xml')
oqparam = mock.Mock()
oqparam.inputs = dict(hazard_curves=fname)
sitecol, hcurves = readinput.get_hcurves(oqparam)
self.assertEqual(len(sitecol), 2)
self.assertEqual(sorted(oqparam.hazard_imtls.items()),
[('PGA', [0.005, 0.007, 0.0137, 0.0337]),
('SA(0.025)', [0.005, 0.007, 0.0137])])
self.assertEqual(str(hcurves), '''\
[([0.098727, 0.098265, 0.094956], [0.098728, 0.098216, 0.094945, 0.092947])
([0.98728, 0.98266, 0.94957], [0.98728, 0.98226, 0.94947, 0.92947])]''')
def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
oq = self.oqparam
if oq.insured_losses:
raise ValueError(
'insured_losses are not supported for classical_risk')
if 'hazard_curves' in oq.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(oq)
self.save_params()
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.assetcol = riskinput.AssetCollection(
self.assets_by_site, self.cost_calculator,
oq.time_event)
self.sitecol, self.assets_by_site = self.assoc_assets_sites(
haz_sitecol)
self.datastore['csm_info'] = fake = source.CompositionInfo.fake()
self.rlzs_assoc = fake.get_rlzs_assoc()
[rlz] = self.rlzs_assoc.realizations
curves_by_rlz = {rlz: haz_curves}
else: # compute hazard or read it from the datastore
super(ClassicalRiskCalculator, self).pre_execute()
logging.info('Preparing the risk input')
curves_by_rlz = {}
nsites = len(self.sitecol.complete)
if 'hcurves' not in self.datastore: # when building short report
return
for key in self.datastore['hcurves']:
pmap = self.datastore['hcurves/' + key]
rlz = self.rlzs_assoc.get_rlz(key)
if rlz is not None: # can be None if a realization is
# missing; this happen in test_case_5
curves_by_rlz[rlz] = pmap.convert(oq.imtls, nsites)
self.riskinputs = self.build_riskinputs(curves_by_rlz)
self.monitor.oqparam = oq
self.N = sum(len(assets) for assets in self.assets_by_site)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = oq.insured_losses
self.Q1 = len(oq.quantile_loss_curves) + 1
def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
oq = self.oqparam
if oq.insured_losses:
raise ValueError(
'insured_losses are not supported for classical_risk')
if 'hazard_curves' in oq.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(oq)
self.save_params()
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.sitecol, self.assetcol = self.assoc_assets_sites(haz_sitecol)
self.datastore['csm_info'] = fake = source.CompositionInfo.fake()
self.rlzs_assoc = fake.get_rlzs_assoc()
rlzs = self.rlzs_assoc.realizations
curves = {rlzs[0]: haz_curves} # there is one realization
else: # compute hazard or read it from the datastore
super(ClassicalRiskCalculator, self).pre_execute()
if 'poes' not in self.datastore: # when building short report
return
logging.info('Combining the hazard curves')
pgetter = calc.PmapGetter(self.datastore)
sids = self.sitecol.complete.sids
with self.monitor('combining hcurves',
measuremem=True,
autoflush=True):
pmaps = pgetter.get_pmaps(sids)
rlzs = self.rlzs_assoc.realizations
curves = {
rlz: pmap.convert(oq.imtls, len(sids))
for rlz, pmap in zip(rlzs, pmaps)
}
with self.monitor('build riskinputs', measuremem=True, autoflush=True):
self.riskinputs = self.build_riskinputs('poe', curves)
self.param = dict(insured_losses=oq.insured_losses,
stats=oq.risk_stats())
self.N = len(self.assetcol)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = oq.insured_losses
self.S = len(oq.risk_stats())
def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
if 'hazard_curves' in self.oqparam.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(self.oqparam)
self.save_params()
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.assetcol = riskinput.AssetCollection(
self.assets_by_site, self.cost_calculator,
self.oqparam.time_event)
self.sitecol, self.assets_by_site = self.assoc_assets_sites(
haz_sitecol)
curves_by_trt_gsim = {(0, 'FromFile'): haz_curves}
self.datastore['csm_info'] = fake = source.CompositionInfo.fake()
self.rlzs_assoc = fake.get_rlzs_assoc()
else: # compute hazard or read it from the datastore
super(ClassicalRiskCalculator, self).pre_execute()
logging.info('Preparing the risk input')
curves_by_trt_gsim = {}
nsites = len(self.sitecol.complete)
if 'poes' not in self.datastore: # when building the short report
return
for key in self.datastore['poes']:
pmap = self.datastore['poes/' + key]
grp_id = int(key)
gsims = self.rlzs_assoc.gsims_by_grp_id[grp_id]
for i, gsim in enumerate(gsims):
curves_by_trt_gsim[grp_id, gsim] = pmap.convert(
self.oqparam.imtls, nsites, i)
self.riskinputs = self.build_riskinputs(curves_by_trt_gsim)
self.monitor.oqparam = self.oqparam
self.N = sum(len(assets) for assets in self.assets_by_site)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = self.oqparam.insured_losses
self.Q1 = len(self.oqparam.quantile_loss_curves) + 1
def pre_execute(self):
"""
Associate the assets to the sites and build the riskinputs.
"""
if 'hazard_curves' in self.oqparam.inputs: # read hazard from file
haz_sitecol, haz_curves = readinput.get_hcurves(self.oqparam)
self.save_params()
self.read_exposure() # define .assets_by_site
self.load_riskmodel()
self.assetcol = riskinput.AssetCollection(
self.assets_by_site, self.cost_calculator,
self.oqparam.time_event)
self.sitecol, self.assets_by_site = self.assoc_assets_sites(
haz_sitecol)
curves_by_trt_gsim = {(0, 'FromFile'): haz_curves}
self.datastore['csm_info'] = fake = source.CompositionInfo.fake()
self.rlzs_assoc = fake.get_rlzs_assoc()
self.save_mesh()
else: # compute hazard or read it from the datastore
super(ClassicalRiskCalculator, self).pre_execute()
logging.info('Preparing the risk input')
curves_by_trt_gsim = {}
for key in self.datastore['poes']:
pmap = self.datastore['poes/' + key]
trt_id = int(key)
gsims = self.rlzs_assoc.gsims_by_trt_id[trt_id]
for i, gsim in enumerate(gsims):
curves_by_trt_gsim[trt_id, gsim] = array_of_curves(
pmap, len(self.sitecol), self.oqparam.imtls, i)
self.riskinputs = self.build_riskinputs(curves_by_trt_gsim)
self.monitor.oqparam = self.oqparam
self.N = sum(len(assets) for assets in self.assets_by_site)
self.L = len(self.riskmodel.loss_types)
self.R = len(self.rlzs_assoc.realizations)
self.I = self.oqparam.insured_losses
self.Q1 = len(self.oqparam.quantile_loss_curves) + 1
