def test_bounding_box(self):
maxdist = IntegrationDistance({'default': [
(3, 30), (4, 40), (5, 100), (6, 200), (7, 300), (8, 400)]})
aae(maxdist('ANY_TRT'), MAX_DISTANCE) # 2000 km
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT')
aae(bb, [-18.2638692, -7.9864, 18.2638692, 27.9864])
aae(maxdist('ANY_TRT', mag=7.1), 400)
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT', mag=7.1)
aae(bb, [-3.6527738, 6.40272, 3.6527738, 13.59728])
aae(maxdist('ANY_TRT', mag=6.9), 300)
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT', mag=6.9)
aae(bb, [-2.7395804, 7.30204, 2.7395804, 12.69796])
def test_bounding_box(self):
maxdist = IntegrationDistance({'default': [
(3, 30), (4, 40), (5, 100), (6, 200), (7, 300), (8, 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])
aae(maxdist('ANY_TRT', mag=7), 400)
bb = maxdist.get_bounding_box(0, 10, 'default', mag=7)
aae(bb, [-2.7395804, 7.30204, 2.7395804, 12.69796])
aae(maxdist('default', mag=6), 200)
bb = maxdist.get_bounding_box(0, 10, 'default', mag=6)
aae(bb, [-1.8263869, 8.20136, 1.8263869, 11.79864])
def make_figure_effect_by_mag(extractors, what):
"""
$ oq plot "effect_by_mag?"
"""
# NB: matplotlib is imported inside since it is a costly import
plt = import_plt()
[ex] = extractors
gsims_by_trt = ex.get('gsims_by_trt', asdict=True)
mags = ex.get('source_mags').array
try:
effect = ex.get('effect')
except KeyError:
onesite = ex.get('sitecol').one()
maximum_distance = IntegrationDistance(ex.oqparam.maximum_distance)
imtls = ex.oqparam.imtls
ebm = get_effect_by_mag(mags, onesite, gsims_by_trt, maximum_distance,
imtls)
effect = numpy.array(list(ebm.values()))
fig, ax = plt.subplots()
trti = 0
for trt in gsims_by_trt:
ax.plot(mags, effect[:, -1, trti], label=trt)
ax.set_xlabel('Mag')
ax.set_ylabel('Intensity')
ax.set_title('Effect at maximum distance')
trti += 1
ax.legend()
return plt
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=IntegrationDistance.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 read_hparams(job_ini):
"""
:param job_ini: path to a job.ini file
:returns: dictionary of hazard parameters
"""
jobdir = os.path.dirname(job_ini)
cp = configparser.ConfigParser()
cp.read([job_ini], encoding='utf8')
params = {}
for sect in cp.sections():
for key, val in cp.items(sect):
if key == 'intensity_measure_types_and_levels':
key = 'imtls'
val = valid.intensity_measure_types_and_levels(val)
elif key == 'maximum_distance':
val = IntegrationDistance.new(val)
elif key == 'sites':
val = valid.coordinates(val)
elif key.endswith('_file'):
val = os.path.join(jobdir, val)
else:
try:
val = ast.literal_eval(val)
except (SyntaxError, ValueError):
if val == 'true':
val = True
elif val == 'false':
val = False
params[key] = val
return params
def __init__(self,
rupture,
sites,
imts,
gsims,
truncation_level=None,
correlation_model=None,
maximum_distance=IntegrationDistance(None)):
if len(sites) == 0:
raise ValueError('No sites')
elif len(imts) == 0:
raise ValueError('No IMTs')
elif len(gsims) == 0:
raise ValueError('No GSIMs')
self.rupture = rupture
self.sites = sites
self.imts = [from_string(imt) for imt in imts]
self.gsims = sorted(gsims)
self.truncation_level = truncation_level
self.correlation_model = correlation_model
self.maximum_distance = maximum_distance
# `rupture` can be a high level rupture object containing a low
# level hazardlib rupture object as a .rupture attribute
if hasattr(rupture, 'rupture'):
rupture = rupture.rupture
self.ctx = ContextMaker(gsims, maximum_distance).make_contexts(
sites, rupture)
def maximum_distance(value):
"""
:param value:
input string corresponding to a valid maximum distance
:returns:
a IntegrationDistance mapping
"""
return IntegrationDistance(MagDist.new(value).max())
def __init__(self, gsims, maximum_distance=IntegrationDistance(None)):
self.gsims = gsims
self.maximum_distance = maximum_distance
for req in self.REQUIRES:
reqset = set()
for gsim in gsims:
reqset.update(getattr(gsim, 'REQUIRES_' + req))
setattr(self, 'REQUIRES_' + req, reqset)
def test_bounding_box(self):
maxdist = IntegrationDistance({
'default': [(3, 30), (4, 40), (5, 100), (6, 200), (7, 300),
(8, 400)]
})
aae(maxdist('ANY_TRT'), MAX_DISTANCE) # 2000 km
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT')
aae(bb, [-18.2638692, -7.9864, 18.2638692, 27.9864])
aae(maxdist('ANY_TRT', mag=7.1), 400)
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT', mag=7.1)
aae(bb, [-3.6527738, 6.40272, 3.6527738, 13.59728])
aae(maxdist('ANY_TRT', mag=6.9), 300)
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT', mag=6.9)
aae(bb, [-2.7395804, 7.30204, 2.7395804, 12.69796])
def maximum_distance(value):
"""
:param value:
input string corresponding to a valid maximum distance
:returns:
a IntegrationDistance mapping
"""
return IntegrationDistance(floatdict(value))
def test_international_date_line_2(self):
# from a bug affecting a calculation in New Zealand
fname = gettemp(characteric_source)
[[src]] = nrml.to_python(fname)
os.remove(fname)
maxdist = IntegrationDistance({'default': 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_MagnitudeDistance_pickleable(self):
md = IntegrationDistance(
dict(default=[(1,
10), (2,
20), (3,
30), (4,
40), (5,
100), (6,
200), (7,
400), (8,
800)]))
md2 = pickle.loads(pickle.dumps(md))
self.assertEqual(md.dic, md2.dic)
def __init__(self, trt, gsims, param=None, monitor=Monitor()):
param = param or {}
self.max_sites_disagg = param.get('max_sites_disagg', 10)
self.collapse_level = param.get('collapse_level', False)
self.point_rupture_bins = param.get('point_rupture_bins', 20)
self.trt = trt
self.gsims = gsims
self.maximum_distance = (param.get('maximum_distance')
or IntegrationDistance({}))
self.trunclevel = param.get('truncation_level')
self.effect = param.get('effect')
for req in self.REQUIRES:
reqset = set()
for gsim in gsims:
reqset.update(getattr(gsim, 'REQUIRES_' + req))
setattr(self, 'REQUIRES_' + req, reqset)
# self.pointsource_distance is a dict mag -> dist, possibly empty
if param.get('pointsource_distance'):
self.pointsource_distance = param['pointsource_distance'][trt]
else:
self.pointsource_distance = {}
self.filter_distance = 'rrup'
if 'imtls' in param:
self.imtls = param['imtls']
elif 'hazard_imtls' in param:
self.imtls = DictArray(param['hazard_imtls'])
else:
self.imtls = {}
self.imts = [imt_module.from_string(imt) for imt in self.imtls]
self.reqv = param.get('reqv')
if self.reqv is not None:
self.REQUIRES_DISTANCES.add('repi')
if hasattr(gsims, 'items'):
# gsims is actually a dict rlzs_by_gsim
# since the ContextMaker must be used on ruptures with the
# same TRT, given a realization there is a single gsim
self.gsim_by_rlzi = {}
for gsim, rlzis in gsims.items():
for rlzi in rlzis:
self.gsim_by_rlzi[rlzi] = gsim
self.mon = monitor
self.ctx_mon = monitor('make_contexts', measuremem=False)
self.loglevels = DictArray(self.imtls)
self.shift_hypo = param.get('shift_hypo')
with warnings.catch_warnings():
# avoid RuntimeWarning: divide by zero encountered in log
warnings.simplefilter("ignore")
for imt, imls in self.imtls.items():
if imt != 'MMI':
self.loglevels[imt] = numpy.log(imls)
def maximum_distance(value):
"""
:param value:
input string corresponding to a valid maximum distance
:returns:
a IntegrationDistance mapping
"""
dic = floatdict(value)
for trt, magdists in dic.items():
if isinstance(magdists, list): # could be a scalar otherwise
magdists.sort() # make sure the list is sorted by magnitude
for mag, dist in magdists: # validate the magnitudes
magnitude(mag)
return IntegrationDistance(dic)
def __init__(self, trt, gsims, param=None, monitor=Monitor()):
param = param or {}
self.max_sites_disagg = param.get('max_sites_disagg', 10)
self.trt = trt
self.gsims = gsims
self.maximum_distance = (
param.get('maximum_distance') or IntegrationDistance({}))
self.trunclevel = param.get('truncation_level')
for req in self.REQUIRES:
reqset = set()
for gsim in gsims:
reqset.update(getattr(gsim, 'REQUIRES_' + req))
setattr(self, 'REQUIRES_' + req, reqset)
self.collapse_factor = param.get('collapse_factor', 3)
self.max_radius = param.get('max_radius')
self.pointsource_distance = param.get('pointsource_distance')
filter_distance = param.get('filter_distance')
if filter_distance is None:
if 'rrup' in self.REQUIRES_DISTANCES:
filter_distance = 'rrup'
elif 'rjb' in self.REQUIRES_DISTANCES:
filter_distance = 'rjb'
else:
filter_distance = 'rrup'
self.filter_distance = filter_distance
self.imtls = param.get('imtls', {})
self.imts = [imt_module.from_string(imt) for imt in self.imtls]
self.reqv = param.get('reqv')
self.REQUIRES_DISTANCES.add(self.filter_distance)
if self.reqv is not None:
self.REQUIRES_DISTANCES.add('repi')
if hasattr(gsims, 'items'):
# gsims is actually a dict rlzs_by_gsim
# since the ContextMaker must be used on ruptures with the
# same TRT, given a realization there is a single gsim
self.gsim_by_rlzi = {}
for gsim, rlzis in gsims.items():
for rlzi in rlzis:
self.gsim_by_rlzi[rlzi] = gsim
self.ctx_mon = monitor('make_contexts', measuremem=False)
self.poe_mon = monitor('get_poes', measuremem=False)
self.pne_mon = monitor('composing pnes', measuremem=False)
self.gmf_mon = monitor('computing mean_std', measuremem=False)
self.loglevels = DictArray(self.imtls)
with warnings.catch_warnings():
# avoid RuntimeWarning: divide by zero encountered in log
warnings.simplefilter("ignore")
for imt, imls in self.imtls.items():
self.loglevels[imt] = numpy.log(imls)
def test_get_bounding_boxes(self):
maxdist = IntegrationDistance({'default': [
(3, 30), (4, 40), (5, 100), (6, 200), (7, 300), (8, 400)]})
sitecol = SiteCollection([
Site(location=Point(10, 20, 30),
vs30=1.2, vs30measured=True,
z1pt0=3.4, z2pt5=5.6, backarc=True),
Site(location=Point(-1.2, -3.4, -5.6),
vs30=55.4, vs30measured=False,
z1pt0=66.7, z2pt5=88.9, backarc=False)])
srcfilter = SourceFilter(sitecol, maxdist)
bb1, bb2 = srcfilter.get_bounding_boxes(mag=4)
# bounding boxes in the form min_lon, min_lat, max_lon, max_lat
aae(bb1, (9.6171855, 19.640272, 10.3828145, 20.359728))
aae(bb2, (-1.5603623, -3.759728, -0.8396377, -3.040272))
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, IntegrationDistance.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_international_date_line(self):
maxdist = IntegrationDistance({'default': [
(3, 30), (4, 40), (5, 100), (6, 200), (7, 300), (8, 400)]})
sitecol = SiteCollection([
Site(location=Point(179, 80),
vs30=1.2, vs30measured=True,
z1pt0=3.4, z2pt5=5.6, backarc=True),
Site(location=Point(-179, 80),
vs30=55.4, vs30measured=False,
z1pt0=66.7, z2pt5=88.9, backarc=False)])
srcfilter = SourceFilter(sitecol, maxdist)
bb1, bb2 = srcfilter.get_bounding_boxes(mag=4)
# bounding boxes in the form min_lon, min_lat, max_lon, max_lat
aae(bb1, (176.928409, 79.640272, 181.071591, 80.359728))
aae(bb2, (-181.071591, 79.640272, -176.928409, 80.359728))
def __init__(self, gsims, maximum_distance=IntegrationDistance(None)):
self.gsims = gsims
self.maximum_distance = maximum_distance
for req in self.REQUIRES:
reqset = set()
for gsim in gsims:
reqset.update(getattr(gsim, 'REQUIRES_' + req))
setattr(self, 'REQUIRES_' + req, reqset)
if hasattr(gsims, 'items'): # gsims is actually a dict rlzs_by_gsim
# since the ContextMaker must be used on ruptures with all the
# same TRT, given a realization there is a single gsim
self.gsim_by_rlzi = {}
for gsim, rlzis in gsims.items():
for rlzi in rlzis:
self.gsim_by_rlzi[rlzi] = gsim
def __init__(self,
trt,
gsims,
maximum_distance=None,
param=None,
monitor=Monitor()):
param = param or {}
self.trt = trt
self.gsims = gsims
self.maximum_distance = maximum_distance or IntegrationDistance({})
self.pointsource_distance = param.get('pointsource_distance', {})
for req in self.REQUIRES:
reqset = set()
for gsim in gsims:
reqset.update(getattr(gsim, 'REQUIRES_' + req))
setattr(self, 'REQUIRES_' + req, reqset)
filter_distance = param.get('filter_distance')
if filter_distance is None:
if 'rrup' in self.REQUIRES_DISTANCES:
filter_distance = 'rrup'
elif 'rjb' in self.REQUIRES_DISTANCES:
filter_distance = 'rjb'
else:
filter_distance = 'rrup'
self.filter_distance = filter_distance
self.reqv = param.get('reqv')
self.REQUIRES_DISTANCES.add(self.filter_distance)
if self.reqv is not None:
self.REQUIRES_DISTANCES.add('repi')
if hasattr(gsims, 'items'):
# gsims is actually a dict rlzs_by_gsim
# since the ContextMaker must be used on ruptures with the
# same TRT, given a realization there is a single gsim
self.gsim_by_rlzi = {}
for gsim, rlzis in gsims.items():
for rlzi in rlzis:
self.gsim_by_rlzi[rlzi] = gsim
self.ir_mon = monitor('iter_ruptures', measuremem=False)
self.ctx_mon = monitor('make_contexts', measuremem=False)
self.poe_mon = monitor('get_poes', measuremem=False)
def test_international_date_line(self):
maxdist = IntegrationDistance({
'default': [(3, 30), (4, 40), (5, 100), (6, 200), (7, 300),
(8, 400)]
})
sitecol = SiteCollection([
Site(location=Point(179, 80),
vs30=1.2,
vs30measured=True,
z1pt0=3.4,
z2pt5=5.6,
backarc=True),
Site(location=Point(-179, 80),
vs30=55.4,
vs30measured=False,
z1pt0=66.7,
z2pt5=88.9,
backarc=False)
])
srcfilter = SourceFilter(sitecol, maxdist)
bb1, bb2 = srcfilter.get_bounding_boxes(mag=4.5)
# bounding boxes in the form min_lon, min_lat, max_lon, max_lat
aae(bb1, (173.8210225, 79.10068, 184.1789775, 80.89932))
aae(bb2, (175.8210225, 79.10068, 186.1789775, 80.89932))
def test_get_bounding_boxes(self):
maxdist = IntegrationDistance({
'default': [(3, 30), (4, 40), (5, 100), (6, 200), (7, 300),
(8, 400)]
})
sitecol = SiteCollection([
Site(location=Point(10, 20, 30),
vs30=1.2,
vs30measured=True,
z1pt0=3.4,
z2pt5=5.6,
backarc=True),
Site(location=Point(-1.2, -3.4, -5.6),
vs30=55.4,
vs30measured=False,
z1pt0=66.7,
z2pt5=88.9,
backarc=False)
])
srcfilter = SourceFilter(sitecol, maxdist)
bb1, bb2 = srcfilter.get_bounding_boxes(mag=4.5)
# bounding boxes in the form min_lon, min_lat, max_lon, max_lat
aae(bb1, (9.0429636, 19.10068, 10.9570364, 20.89932))
aae(bb2, (-2.1009057, -4.29932, -0.2990943, -2.50068))
def test_maximum_magnitude(self):
maxdist = IntegrationDistance.new(
'[(4, 200), (7, 200), (7.01, 0), (8, 0)]')
interp = maxdist('default')
aae(interp([5, 6, 7, 7.2, 8]), [200., 200., 200., 0., 0.])
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=IntegrationDistance.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)
def test_point_sources(self):
sources = [
openquake.hazardlib.source.PointSource(
source_id='point1', name='point1',
tectonic_region_type="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="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 = {"Active Shallow Crust": SadighEtAl1997()}
truncation_level = 1
imts = {'PGA': [0.1, 0.5, 1.3]}
s_filter = SourceFilter(sitecol, IntegrationDistance.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
def test_bounding_box(self):
maxdist = IntegrationDistance({'default': 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, contexts
from openquake.hazardlib.cross_correlation import BakerJayaram2008
from openquake.hazardlib.calc.filters import IntegrationDistance
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=IntegrationDistance.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),
def test_bounding_box(self):
maxdist = IntegrationDistance.new('400')
bb = maxdist.get_bounding_box(0, 10, 'ANY_TRT')
aae(bb, [-3.6527738, 6.40272, 3.6527738, 13.59728])
