def test_single_site(self):
# NB: the performance of get_mean_std is totally dominated by two
# concomitant factors:
# 1) source splitting (do not split the area source)
# 2) collect the contexts in a single array
# together they give a 200x speedup
# numba is totally useless
site = Site(Point(0, 0),
vs30=760.,
z1pt0=48.0,
z2pt5=0.607,
vs30measured=True)
sitecol = SiteCollection([site])
imtls = {"PGA": [.123]}
for period in numpy.arange(.1, 1.3, .1):
imtls['SA(%.2f)' % period] = [.123]
assert len(imtls) == 13 # 13 periods
oq = unittest.mock.Mock(imtls=DictArray(imtls),
maximum_distance=MagDepDistance.new('300'))
mon = Monitor()
hcurve = calc_hazard_curve(sitecol, asource, [ExampleA2021()], oq, mon)
for child in mon.children:
print(child)
got = hcurve.array[:, 0]
exp = [
0.103379, 0.468937, 0.403896, 0.278772, 0.213645, 0.142985,
0.103438, 0.079094, 0.062861, 0.051344, 0.04066, 0.031589, 0.024935
]
numpy.testing.assert_allclose(got, exp, atol=1E-5)
def test_international_date_line(self):
# from a bug affecting a calculation in New Zealand
fname = gettemp(characteric_source)
[[src]] = nrml.to_python(fname)
os.remove(fname)
maxdist = MagDepDistance.new('200')
sitecol = SiteCollection([
Site(location=Point(176.919, -39.489),
vs30=760, vs30measured=True, z1pt0=100, z2pt5=5)])
srcfilter = SourceFilter(sitecol, maxdist)
sites = srcfilter.get_close_sites(src)
self.assertIsNotNone(sites)
def test_two_sites(self):
site1 = Site(Point(0, 0),
vs30=760.,
z1pt0=48.0,
z2pt5=0.607,
vs30measured=True)
site2 = Site(Point(0, 0.5),
vs30=760.,
z1pt0=48.0,
z2pt5=0.607,
vs30measured=True)
sitecol = SiteCollection([site1, site2])
srcfilter = SourceFilter(sitecol, MagDepDistance.new('200'))
imtls = {"PGA": [.123]}
for period in numpy.arange(.1, .5, .1):
imtls['SA(%.2f)' % period] = [.123]
assert len(imtls) == 5 # 5 periods
gsim_by_trt = {'Stable Continental Crust': ExampleA2021()}
hcurves = calc_hazard_curves([asource], srcfilter, DictArray(imtls),
gsim_by_trt)
print(hcurves)
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, 2, 3),
openquake.hazardlib.site.Site(Point(10, 16), 2, 2, 3),
openquake.hazardlib.site.Site(Point(10, 10.6, 1), 3, 2, 3),
openquake.hazardlib.site.Site(Point(10, 10.7, -1), 4, 2, 3)]
sitecol = openquake.hazardlib.site.SiteCollection(sites)
gsims = {const.TRT.ACTIVE_SHALLOW_CRUST: SadighEtAl1997()}
truncation_level = 1
imts = {'PGA': [0.1, 0.5, 1.3]}
s_filter = SourceFilter(sitecol, MagDepDistance.new('30'))
result = calc_hazard_curves(
sources, s_filter, imts, gsims, truncation_level)['PGA']
# 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(result.shape, (4, 3)) # 4 sites, 3 levels
numpy.testing.assert_allclose(result[0], 0) # no contrib to site 1
numpy.testing.assert_allclose(result[1], 0) # no contrib to site 2
# test that depths are kept after filtering (sites 3 and 4 remain)
s_filter = SourceFilter(sitecol, MagDepDistance.new('100'))
numpy.testing.assert_array_equal(
s_filter.get_close_sites(sources[0]).depths, ([1, -1]))
def test_bounding_box(self):
maxdist = MagDepDistance.new('400')
aae(maxdist('ANY_TRT'), 400)
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT')
aae(bb, [-3.6527738, 6.40272, 3.6527738, 13.59728])
from openquake.hazardlib import read_input, valid
from openquake.hazardlib.cross_correlation import BakerJayaram2008
from openquake.hazardlib.calc.filters import MagDepDistance
OVERWRITE_EXPECTED = False
CWD = os.path.dirname(__file__)
SOURCES_XML = os.path.join(CWD, 'data', 'sm01.xml')
GSIM_XML = os.path.join(CWD, 'data', 'lt02.xml')
PARAM = dict(source_model_file=SOURCES_XML,
gsim_logic_tree_file=GSIM_XML,
sites=[(0, -0.8)],
reference_vs30_value=600,
reference_depth_to_2pt5km_per_sec=5,
reference_depth_to_1pt0km_per_sec=100,
maximum_distance=MagDepDistance.new('200'),
rupture_mesh_spacing=5.,
width_of_mfd_bin=1.,
investigation_time=1,
truncation_level=3,
cross_correl=BakerJayaram2008(),
imtls={"SA(0.05)": valid.logscale(0.005, 2.13, 45),
"SA(0.075)": valid.logscale(0.005, 2.13, 45),
"SA(0.1)": valid.logscale(0.005, 2.13, 45),
"SA(0.15)": valid.logscale(0.005, 2.13, 45),
"SA(0.2)": valid.logscale(0.005, 2.13, 45),
"SA(0.25)": valid.logscale(0.005, 2.13, 45),
"SA(0.3)": valid.logscale(0.005, 2.13, 45),
"SA(0.5)": valid.logscale(0.005, 2.13, 45),
"SA(0.75)": valid.logscale(0.005, 2.13, 45),
"SA(1.0)": valid.logscale(0.005, 2.13, 45),
def main(params):
# example with 2x2=4 realizations with weights .36, .24, .24, .16
inp = read_input(params)
print(inp)
print(inp.gsim_lt.get_rlzs_by_gsim_trt())
acc = AccumDict(accum=[])
ebrs = sample_ebruptures(inp.groups, inp.cmakerdict)
ne = sum(ebr.n_occ for ebr in ebrs)
print('There are %d ruptures and %d events' % (len(ebrs), ne))
df = get_ebr_df(ebrs, inp.cmakerdict)
print(df.groupby('rlz').count()) # there are 8, 9, 11, 8 events per rlz
for ebr in ebrs:
cmaker = inp.cmakerdict[ebr.rupture.tectonic_region_type]
gmf_dict, _ = GmfComputer(ebr, inp.sitecol, cmaker).compute_all()
acc += gmf_dict
print(pandas.DataFrame(acc))
if __name__ == '__main__':
params = dict(maximum_distance=MagDepDistance.new('200'),
imtls={'PGA': [0]},
source_model_file="source_model.xml",
area_source_discretization=10,
ses_seed=24,
ses_per_logic_tree_path=20,
investigation_time=1,
site_model_file="site_model.csv",
gsim_logic_tree_file="gmpe_logic_tree.xml")
main(params)