def setUp(self):
inputs = [("fragility", ""), ("exposure", "")]
self.job = self.setup_classic_job(inputs=inputs)
kvs.mark_job_as_current(self.job.id)
kvs.cache_gc(self.job.id)
self.site = Site(1.0, 1.0)
block = Block(self.job.id, BLOCK_ID, [self.site])
block.to_kvs()
# this region contains a single site, that is exactly
# a site with longitude == 1.0 and latitude == 1.0
params = {"REGION_VERTEX": "1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0",
"REGION_GRID_SPACING": "0.5", "BASE_PATH": ".",
"OUTPUT_DIR": "."}
self.job_ctxt = JobContext(params, self.job.id, oq_job=self.job)
self.em = self._store_em()
self._store_gmvs([0.40, 0.30, 0.45, 0.35, 0.40])
self.calculator = ScenarioDamageRiskCalculator(self.job_ctxt)
# just stubbing out some preprocessing stuff...
ScenarioDamageRiskCalculator.store_exposure_assets = lambda self: None
ScenarioDamageRiskCalculator.store_fragility_model = lambda self: None
ScenarioDamageRiskCalculator.partition = lambda self: None
def test_block_kvs_serialization(self):
# Test that a Block is properly serialized/deserialized from the cache.
job_id = 7
block_id = 0
expected_block = Block(job_id, block_id,
[shapes.Site(1.0, 1.0), shapes.Site(2.0, 2.0)])
expected_block.to_kvs()
actual_block = Block.from_kvs(job_id, block_id)
self.assertEqual(expected_block, actual_block)
# The sites are not compared in Block.__eq__; we need to check those
# also.
self.assertEqual(expected_block.sites, actual_block.sites)
def test_block_kvs_serialization(self):
# Test that a Block is properly serialized/deserialized from the cache.
job_id = 7
block_id = 0
expected_block = Block(job_id, block_id,
[shapes.Site(1.0, 1.0),
shapes.Site(2.0, 2.0)])
expected_block.to_kvs()
actual_block = Block.from_kvs(job_id, block_id)
self.assertEqual(expected_block, actual_block)
# The sites are not compared in Block.__eq__; we need to check those
# also.
self.assertEqual(expected_block.sites, actual_block.sites)
def test_compute_bcr(self):
cfg_path = helpers.demo_file(
'probabilistic_event_based_risk/config.gem')
helpers.delete_profile(self.job)
job_profile, params, sections = engine.import_job_profile(
cfg_path, self.job)
job_profile.calc_mode = 'event_based_bcr'
job_profile.interest_rate = 0.05
job_profile.asset_life_expectancy = 50
job_profile.region = GEOSGeometry(shapes.polygon_ewkt_from_coords(
'0.0, 0.0, 0.0, 2.0, 2.0, 2.0, 2.0, 0.0'))
job_profile.region_grid_spacing = 0.1
job_profile.maximum_distance = 200.0
job_profile.gmf_random_seed = None
job_profile.save()
params.update(dict(CALCULATION_MODE='Event Based BCR',
INTEREST_RATE='0.05',
ASSET_LIFE_EXPECTANCY='50',
MAXIMUM_DISTANCE='200.0',
REGION_VERTEX=('0.0, 0.0, 0.0, 2.0, '
'2.0, 2.0, 2.0, 0.0'),
REGION_GRID_SPACING='0.1'))
job_ctxt = engine.JobContext(
params, self.job_id, sections=sections, oq_job_profile=job_profile)
calculator = eb_core.EventBasedRiskCalculator(job_ctxt)
self.block_id = 7
SITE = shapes.Site(1.0, 1.0)
block = Block(self.job_id, self.block_id, (SITE, ))
block.to_kvs()
location = GEOSGeometry(SITE.point.to_wkt())
asset = models.ExposureData(exposure_model=self.emdl, taxonomy="ID",
asset_ref=22.61, stco=1, reco=123.45,
site=location)
asset.save()
calculator.compute_risk(self.block_id)
result_key = kvs.tokens.bcr_block_key(self.job_id, self.block_id)
result = kvs.get_value_json_decoded(result_key)
expected_result = {'bcr': 0.0, 'eal_original': 0.0,
'eal_retrofitted': 0.0}
helpers.assertDeepAlmostEqual(
self, [[[1, 1], [[expected_result, "22.61"]]]], result)
def _compute_risk_classical_psha_setup(self):
SITE = shapes.Site(1.0, 1.0)
# deletes all keys from kvs
kvs.get_client().flushall()
# at the moment the hazard part doesn't do exp on the 'x'
# so it's done on the risk part. To adapt the calculation
# we do the reverse of the exp, i.e. log(x)
self.hazard_curve = [
(SITE,
{'IMLValues': [0.001, 0.080, 0.170, 0.260, 0.360,
0.550, 0.700],
'PoEValues': [0.99, 0.96, 0.89, 0.82, 0.70, 0.40, 0.01],
'statistics': 'mean'})]
# Vitor provided this Vulnerability Function
imls_1 = [0.03, 0.04, 0.07, 0.1, 0.12, 0.22, 0.37, 0.52]
loss_ratios_1 = [0.001, 0.022, 0.051, 0.08, 0.1, 0.2, 0.405, 0.700]
covs_1 = [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]
self.vuln_function = vulnerability_function.VulnerabilityFunction(
imls_1, loss_ratios_1, covs_1, "LN")
imls_2 = [0.1, 0.2, 0.4, 0.6]
loss_ratios_2 = [0.05, 0.08, 0.2, 0.4]
covs_2 = [0.5, 0.3, 0.2, 0.1]
self.vuln_function_2 = vulnerability_function.VulnerabilityFunction(
imls_2, loss_ratios_2, covs_2, "LN")
self.asset_1 = {"taxonomy": "ID", "assetValue": 124.27}
self.region = shapes.RegionConstraint.from_simple(
(0.0, 0.0), (2.0, 2.0))
block = Block(self.job_id, self.block_id, (SITE, ))
block.to_kvs()
writer = hazard.HazardCurveDBWriter('test_path.xml', self.job_id)
writer.serialize(self.hazard_curve)
kvs.set_value_json_encoded(
kvs.tokens.vuln_key(self.job_id),
{"ID": self.vuln_function.to_json()})
kvs.set_value_json_encoded(
kvs.tokens.vuln_key(self.job_id, retrofitted=True),
{"ID": self.vuln_function.to_json()})
