def test_source_errors(self):
# exercise `hazard_curves_poissonian` in the case of an exception,
# whereby we expect the source_id to be reported in the error message
fail_source = self.FailSource(self.source2.source_id,
self.source2.ruptures,
self.source2.time_span)
sources = iter([self.source1, fail_source])
with self.assertRaises(ValueError) as ae:
hazard_curves(sources, self.sites, self.imts, self.gsims,
self.truncation_level)
expected_error = (
'An error occurred with source id=2. Error: Something bad happened'
)
self.assertEqual(expected_error, ae.exception.message)
def reference_psha_calculation_openquake():
"""
Sets up the reference PSHA calculation calling OpenQuake directly. All
subsequent implementations should match this example
"""
# Site model - 3 Sites
site_model = SiteCollection([
Site(Point(30.0, 30.0), 760., True, 1.0, 1.0, 1),
Site(Point(30.25, 30.25), 760., True, 1.0, 1.0, 2),
Site(Point(30.4, 30.4), 760., True, 1.0, 1.0, 2)])
# Source Model Two Point Sources
mfd_1 = TruncatedGRMFD(4.5, 8.0, 0.1, 4.0, 1.0)
mfd_2 = TruncatedGRMFD(4.5, 7.5, 0.1, 3.5, 1.1)
source_model = [PointSource('001', 'Point1', 'Active Shallow Crust',
mfd_1, 1.0, WC1994(), 1.0, PoissonTOM(50.0),
0.0, 30.0, Point(30.0, 30.5),
PMF([(1.0, NodalPlane(0.0, 90.0, 0.0))]),
PMF([(1.0, 10.0)])),
PointSource('002', 'Point2', 'Active Shallow Crust',
mfd_2, 1.0, WC1994(), 1.0, PoissonTOM(50.0),
0.0, 30.0, Point(30.0, 30.5),
PMF([(1.0, NodalPlane(0.0, 90.0, 0.0))]),
PMF([(1.0, 10.0)]))]
imts = {PGA(): [0.01, 0.1, 0.2, 0.5, 0.8],
SA(period=0.5, damping=5.0): [0.01, 0.1, 0.2, 0.5, 0.8]}
# Akkar & Bommer (2010) GMPE
gsims = {'Active Shallow Crust': gsim.akkar_bommer_2010.AkkarBommer2010()}
truncation_level = None
return hazard_curves(source_model, site_model, imts, gsims,
truncation_level)
def test1(self):
site1_pga_poe_expected = [0.0639157, 0.03320212, 0.02145989]
site2_pga_poe_expected = [0.06406232, 0.02965879, 0.01864331]
site1_pgd_poe_expected = [0.16146619, 0.1336553]
site2_pgd_poe_expected = [0.15445961, 0.13437589]
curves = hazard_curves(self.sources, self.sites, self.imts,
self.gsims, self.truncation_level)
self.assertIsInstance(curves, dict)
self.assertEqual(set(curves.keys()), set([imt.PGA(), imt.PGD()]))
pga_curves = curves[imt.PGA()]
self.assertIsInstance(pga_curves, numpy.ndarray)
self.assertEqual(pga_curves.shape, (2, 3)) # two sites, three IMLs
site1_pga_poe, site2_pga_poe = pga_curves
self.assertTrue(numpy.allclose(site1_pga_poe, site1_pga_poe_expected),
str(site1_pga_poe))
self.assertTrue(numpy.allclose(site2_pga_poe, site2_pga_poe_expected),
str(site2_pga_poe))
pgd_curves = curves[imt.PGD()]
self.assertIsInstance(pgd_curves, numpy.ndarray)
self.assertEqual(pgd_curves.shape, (2, 2)) # two sites, two IMLs
site1_pgd_poe, site2_pgd_poe = pgd_curves
self.assertTrue(numpy.allclose(site1_pgd_poe, site1_pgd_poe_expected),
str(site1_pgd_poe))
self.assertTrue(numpy.allclose(site2_pgd_poe, site2_pgd_poe_expected),
str(site2_pgd_poe))
def calculate_hazard(self, num_workers=DEFAULT_WORKERS,
num_src_workers=1):
"""
Calculates the hazard
:param int num_workers:
Number of workers for parallel calculation
:param int num_src_workers:
Number of elements per worker
"""
return hazard_curve.hazard_curves(self.source_model, self.sites,
self.imts, self.gmpes,
self.truncation_level,
self.src_filter, self.rup_filter)
def test_point_sources(self):
sources = [
openquake.hazardlib.source.PointSource(
source_id='point1', name='point1',
tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
min_mag=4, bin_width=1, occurrence_rates=[5]
),
nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
(1, openquake.hazardlib.geo.NodalPlane(strike=0.0,
dip=90.0,
rake=0.0))
]),
hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=10.0,
magnitude_scaling_relationship=
openquake.hazardlib.scalerel.PeerMSR(),
rupture_aspect_ratio=2,
temporal_occurrence_model=PoissonTOM(1.),
rupture_mesh_spacing=1.0,
location=Point(10, 10)
),
openquake.hazardlib.source.PointSource(
source_id='point2', name='point2',
tectonic_region_type=const.TRT.ACTIVE_SHALLOW_CRUST,
mfd=openquake.hazardlib.mfd.EvenlyDiscretizedMFD(
min_mag=4, bin_width=2, occurrence_rates=[5, 6, 7]
),
nodal_plane_distribution=openquake.hazardlib.pmf.PMF([
(1, openquake.hazardlib.geo.NodalPlane(strike=0,
dip=90,
rake=0.0)),
]),
hypocenter_distribution=openquake.hazardlib.pmf.PMF([(1, 10)]),
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=10.0,
magnitude_scaling_relationship=
openquake.hazardlib.scalerel.PeerMSR(),
rupture_aspect_ratio=2,
temporal_occurrence_model=PoissonTOM(1.),
rupture_mesh_spacing=1.0,
location=Point(10, 11)
),
]
sites = [openquake.hazardlib.site.Site(Point(11, 10), 1, True, 2, 3),
openquake.hazardlib.site.Site(Point(10, 16), 2, True, 2, 3),
openquake.hazardlib.site.Site(Point(10, 10.6), 3, True, 2, 3),
openquake.hazardlib.site.Site(Point(10, 10.7), 4, True, 2, 3)]
sitecol = openquake.hazardlib.site.SiteCollection(sites)
from openquake.hazardlib.gsim.sadigh_1997 import SadighEtAl1997
gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: SadighEtAl1997()}
truncation_level = 1
imts = {openquake.hazardlib.imt.PGA(): [0.1, 0.5, 1.3]}
from openquake.hazardlib.calc import filters
source_site_filter = self.SitesCounterSourceFilter(
filters.source_site_distance_filter(30)
)
rupture_site_filter = self.SitesCounterRuptureFilter(
filters.rupture_site_distance_filter(30)
)
hazard_curves(
iter(sources), sitecol, imts, gsims, truncation_level,
source_site_filter=source_site_filter,
rupture_site_filter=rupture_site_filter
)
# there are two sources and four sites. The first source contains only
# one rupture, the second source contains three ruptures.
#
# the first source has 'maximum projection radius' of 0.707 km
# the second source has 'maximum projection radius' of 500.0 km
#
# the epicentral distances for source 1 are: [ 109.50558394,
# 667.16955987, 66.71695599, 77.83644865]
# the epicentral distances for source 2 are: [ 155.9412148 ,
# 555.97463322, 44.47797066, 33.35847799]
#
# Considering that the source site filtering distance is set to 30 km,
# for source 1, all sites have epicentral distance larger than
# 0.707 + 30 km. This means that source 1 ('point 1') is not considered
# in the calculation because too far.
# for source 2, the 1st, 3rd and 4th sites have epicentral distances
# smaller than 500.0 + 30 km. This means that source 2 ('point 2') is
# considered in the calculation for site 1, 3, and 4.
#
# JB distances for rupture 1 in source 2 are: [ 155.43860273,
# 555.26752644, 43.77086388, 32.65137121]
# JB distances for rupture 2 in source 2 are: [ 150.98882575,
# 548.90356541, 37.40690285, 26.28741018]
# JB distances for rupture 3 in source 2 are: [ 109.50545819,
# 55.97463322, 0. , 0. ]
#
# Considering that the rupture site filtering distance is set to 30 km,
# rupture 1 (magnitude 4) is not considered because too far, rupture 2
# (magnitude 6) affect only the 4th site, rupture 3 (magnitude 8)
# affect the 3rd and 4th sites.
self.assertEqual(source_site_filter.counts,
[('point2', [1, 3, 4])])
self.assertEqual(rupture_site_filter.counts,
[(6, [4]), (8, [3, 4])])