def get_background_sources(self):
"""
Turn the background model of a given branch into a set of point sources
"""
background_sids = self.get_background_sids()
with h5py.File(self.source_file, "r") as hdf5:
grid_loc = "/".join(["Grid", self.ukey["grid_key"]])
# for instance Grid/FM0_0_MEANFS_MEANMSR_MeanRates
mags = hdf5[grid_loc + "/Magnitude"][()]
mmax = hdf5[grid_loc + "/MMax"][background_sids]
rates = hdf5[grid_loc + "/RateArray"][background_sids, :]
locations = hdf5["Grid/Locations"][background_sids, :]
sources = []
for i, bg_idx in enumerate(background_sids):
src_id = "_".join([self.ukey["grid_key"], str(bg_idx)])
src_name = "|".join([self.ukey["total_key"], str(bg_idx)])
mag_idx = (self.min_mag <= mags) & (mags < mmax[i])
src_mags = mags[mag_idx]
src_mfd = EvenlyDiscretizedMFD(src_mags[0],
src_mags[1] - src_mags[0],
rates[i, mag_idx].tolist())
ps = PointSource(src_id, src_name, self.tectonic_region_type,
src_mfd, self.mesh_spacing, self.msr,
self.aspect, self.tom, self.usd, self.lsd,
Point(locations[i, 0],
locations[i, 1]), self.npd, self.hdd)
ps.checksum = zlib.adler32(pickle.dumps(vars(ps), protocol=4))
ps._wkt = ps.wkt()
ps.id = self.id
ps.et_id = self.et_id
ps.num_ruptures = ps.count_ruptures()
ps.nsites = 1 # anything <> 0 goes
sources.append(ps)
return sources
def setUp(self):
"""
"""
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)
self.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)]))
]
self.sites = 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)
])
self.gsims = {'Active Shallow Crust': 'AkkarBommer2010'}
self.imts = ['PGA', 'SA(0.5)']
self.imls = [[0.01, 0.1, 0.2, 0.5, 0.8]]
def _get_rupture(self, min_mag, max_mag, hypocenter_depth,
aspect_ratio, dip, rupture_mesh_spacing,
upper_seismogenic_depth=2,
lower_seismogenic_depth=16):
source_id = name = 'test-source'
trt = TRT.ACTIVE_SHALLOW_CRUST
mfd = TruncatedGRMFD(a_val=2, b_val=1, min_mag=min_mag,
max_mag=max_mag, bin_width=1)
location = Point(0, 0)
nodal_plane = NodalPlane(strike=45, dip=dip, rake=-123.23)
nodal_plane_distribution = PMF([(1, nodal_plane)])
hypocenter_distribution = PMF([(1, hypocenter_depth)])
magnitude_scaling_relationship = PeerMSR()
rupture_aspect_ratio = aspect_ratio
point_source = PointSource(
source_id, name, trt, mfd, rupture_mesh_spacing,
magnitude_scaling_relationship, rupture_aspect_ratio,
upper_seismogenic_depth, lower_seismogenic_depth,
location, nodal_plane_distribution, hypocenter_distribution
)
tom = PoissonTOM(time_span=50)
ruptures = list(point_source.iter_ruptures(tom))
self.assertEqual(len(ruptures), 1)
[rupture] = ruptures
self.assertIs(rupture.temporal_occurrence_model, tom)
self.assertIs(rupture.tectonic_region_type, trt)
self.assertEqual(rupture.rake, nodal_plane.rake)
self.assertIsInstance(rupture.surface, PlanarSurface)
self.assertEqual(rupture.surface.mesh_spacing, rupture_mesh_spacing)
return rupture
def get_background_sources(self, src_filter):
"""
Turn the background model of a given branch into a set of point sources
:param src_filter:
SourceFilter instance
"""
background_sids = self.get_background_sids(src_filter)
with h5py.File(self.source_file, "r") as hdf5:
grid_loc = "/".join(["Grid", self.idx_set["grid_key"]])
mags = hdf5[grid_loc + "/Magnitude"].value
mmax = hdf5[grid_loc + "/MMax"][background_sids]
rates = hdf5[grid_loc + "/RateArray"][background_sids, :]
locations = hdf5["Grid/Locations"][background_sids, :]
sources = []
for i, bg_idx in enumerate(background_sids):
src_id = "_".join([self.idx_set["grid_key"], str(bg_idx)])
src_name = "|".join([self.idx_set["total_key"], str(bg_idx)])
# Get MFD
mag_idx = numpy.logical_and(mags >= self.min_mag,
mags < mmax[i])
src_mags = mags[mag_idx]
src_rates = rates[i, :]
src_mfd = EvenlyDiscretizedMFD(src_mags[0],
src_mags[1] - src_mags[0],
src_rates[mag_idx].tolist())
ps = PointSource(src_id, src_name, self.tectonic_region_type,
src_mfd, self.mesh_spacing, self.msr,
self.aspect, self.tom, self.usd, self.lsd,
Point(locations[i, 0],
locations[i, 1]), self.npd, self.hdd)
ps.src_group_id = self.src_group_id
sources.append(ps)
return sources
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(0.5)': [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 calc_hazard_curves(source_model, site_model, imts, gsims,
truncation_level)
def example_calc(apply):
sitecol = SiteCollection([
Site(Point(30.0, 30.0), 760., 1.0, 1.0),
Site(Point(30.25, 30.25), 760., 1.0, 1.0),
Site(Point(30.4, 30.4), 760., 1.0, 1.0)
])
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)
sources = [
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)]))
]
imtls = {
'PGA': [0.01, 0.1, 0.2, 0.5, 0.8],
'SA(0.5)': [0.01, 0.1, 0.2, 0.5, 0.8]
}
gsims = {'Active Shallow Crust': AkkarBommer2010()}
return calc_hazard_curves(sources,
sitecol,
imtls,
gsims,
apply=apply,
filter_distance='rrup')
def _get_rupture(self, min_mag, max_mag, hypocenter_depth,
aspect_ratio, dip, rupture_mesh_spacing,
upper_seismogenic_depth=2,
lower_seismogenic_depth=16):
source_id = name = 'test-source'
trt = TRT.ACTIVE_SHALLOW_CRUST
mfd = TruncatedGRMFD(a_val=2, b_val=1, min_mag=min_mag,
max_mag=max_mag, bin_width=1)
location = Point(0, 0)
nodal_plane = NodalPlane(strike=45, dip=dip, rake=-123.23)
nodal_plane_distribution = PMF([(1, nodal_plane)])
hypocenter_distribution = PMF([(1, hypocenter_depth)])
magnitude_scaling_relationship = PeerMSR()
rupture_aspect_ratio = aspect_ratio
tom = PoissonTOM(time_span=50)
point_source = PointSource(
source_id, name, trt, mfd, rupture_mesh_spacing,
magnitude_scaling_relationship, rupture_aspect_ratio, tom,
upper_seismogenic_depth, lower_seismogenic_depth,
location, nodal_plane_distribution, hypocenter_distribution
)
ruptures = list(point_source.iter_ruptures())
self.assertEqual(len(ruptures), 1)
[rupture] = ruptures
self.assertIs(rupture.temporal_occurrence_model, tom)
self.assertIs(rupture.tectonic_region_type, trt)
self.assertEqual(rupture.rake, nodal_plane.rake)
self.assertIsInstance(rupture.surface, PlanarSurface)
return rupture
def __iter__(self):
"""
Split an area source into a generator of point sources.
MFDs will be rescaled appropriately for the number of points in the
area mesh.
"""
mesh = self.polygon.discretize(self.area_discretization)
num_points = len(mesh)
area_mfd = self.mfd
if isinstance(area_mfd, mfd.TruncatedGRMFD):
new_mfd = mfd.TruncatedGRMFD(a_val=area_mfd.a_val -
math.log10(num_points),
b_val=area_mfd.b_val,
bin_width=area_mfd.bin_width,
min_mag=area_mfd.min_mag,
max_mag=area_mfd.max_mag)
elif isinstance(area_mfd, mfd.EvenlyDiscretizedMFD):
new_occur_rates = [
x / num_points for x in area_mfd.occurrence_rates
]
new_mfd = mfd.EvenlyDiscretizedMFD(
min_mag=area_mfd.min_mag,
bin_width=area_mfd.bin_width,
occurrence_rates=new_occur_rates)
elif isinstance(area_mfd, mfd.ArbitraryMFD):
new_occur_rates = [
x / num_points for x in area_mfd.occurrence_rates
]
new_mfd = mfd.ArbitraryMFD(magnitudes=area_mfd.magnitudes,
occurrence_rates=new_occur_rates)
elif isinstance(area_mfd, mfd.YoungsCoppersmith1985MFD):
new_mfd = mfd.YoungsCoppersmith1985MFD.from_characteristic_rate(
area_mfd.min_mag, area_mfd.b_val, area_mfd.char_mag,
area_mfd.char_rate / num_points, area_mfd.bin_width)
else:
raise TypeError('Unknown MFD: %s' % area_mfd)
for i, (lon, lat) in enumerate(zip(mesh.lons, mesh.lats)):
pt = PointSource(
# Generate a new ID and name
source_id='%s:%s' % (self.source_id, i),
name=self.name,
tectonic_region_type=self.tectonic_region_type,
mfd=new_mfd,
rupture_mesh_spacing=self.rupture_mesh_spacing,
magnitude_scaling_relationship=self.
magnitude_scaling_relationship,
rupture_aspect_ratio=self.rupture_aspect_ratio,
upper_seismogenic_depth=self.upper_seismogenic_depth,
lower_seismogenic_depth=self.lower_seismogenic_depth,
location=geo.Point(lon, lat),
nodal_plane_distribution=self.nodal_plane_distribution,
hypocenter_distribution=self.hypocenter_distribution,
temporal_occurrence_model=self.temporal_occurrence_model)
pt.num_ruptures = pt.count_ruptures()
yield pt
def __iter__(self):
"""
Split an area source into a generator of point sources.
MFDs will be rescaled appropriately for the number of points in the
area mesh.
"""
mesh = self.polygon.discretize(self.area_discretization)
num_points = len(mesh)
area_mfd = self.mfd
if isinstance(area_mfd, mfd.TruncatedGRMFD):
new_mfd = mfd.TruncatedGRMFD(
a_val=area_mfd.a_val - math.log10(num_points),
b_val=area_mfd.b_val,
bin_width=area_mfd.bin_width,
min_mag=area_mfd.min_mag,
max_mag=area_mfd.max_mag)
elif isinstance(area_mfd, mfd.EvenlyDiscretizedMFD):
new_occur_rates = [x/num_points for x in area_mfd.occurrence_rates]
new_mfd = mfd.EvenlyDiscretizedMFD(
min_mag=area_mfd.min_mag,
bin_width=area_mfd.bin_width,
occurrence_rates=new_occur_rates)
elif isinstance(area_mfd, mfd.ArbitraryMFD):
new_occur_rates = [x/num_points for x in area_mfd.occurrence_rates]
new_mfd = mfd.ArbitraryMFD(
magnitudes=area_mfd.magnitudes,
occurrence_rates=new_occur_rates)
elif isinstance(area_mfd, mfd.YoungsCoppersmith1985MFD):
new_mfd = mfd.YoungsCoppersmith1985MFD.from_characteristic_rate(
area_mfd.min_mag, area_mfd.b_val, area_mfd.char_mag,
area_mfd.char_rate / num_points, area_mfd.bin_width)
else:
raise TypeError('Unknown MFD: %s' % area_mfd)
for i, (lon, lat) in enumerate(zip(mesh.lons, mesh.lats)):
pt = PointSource(
# Generate a new ID and name
source_id='%s:%s' % (self.source_id, i),
name=self.name,
tectonic_region_type=self.tectonic_region_type,
mfd=new_mfd,
rupture_mesh_spacing=self.rupture_mesh_spacing,
magnitude_scaling_relationship=
self.magnitude_scaling_relationship,
rupture_aspect_ratio=self.rupture_aspect_ratio,
upper_seismogenic_depth=self.upper_seismogenic_depth,
lower_seismogenic_depth=self.lower_seismogenic_depth,
location=geo.Point(lon, lat),
nodal_plane_distribution=self.nodal_plane_distribution,
hypocenter_distribution=self.hypocenter_distribution,
temporal_occurrence_model=self.temporal_occurrence_model)
pt.num_ruptures = pt.count_ruptures()
yield pt
def test_495_km(self):
rup = self._make_rupture(5, 8, 5) # 4.68 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=495, sites=self.sitecol)
numpy.testing.assert_array_equal(filtered.indices, [0, 1, 2, 3])
rup = self._make_rupture(7, 10, 30) # 5.8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=495, sites=self.sitecol)
self.assertIs(filtered.indices, None)
self.assertIs(filtered, self.sitecol)
def __iter__(self):
for i, (mfd, point) in enumerate(zip(self.mfd, self.mesh)):
name = '%s:%s' % (self.source_id, i)
ps = PointSource(
name, name, self.tectonic_region_type, mfd,
self.rupture_mesh_spacing, self.magnitude_scaling_relationship,
self.rupture_aspect_ratio, self.temporal_occurrence_model,
self.upper_seismogenic_depth, self.lower_seismogenic_depth,
point, self.nodal_plane_distribution,
self.hypocenter_distribution)
ps.num_ruptures = ps.count_ruptures()
yield ps
def test_zero_integration_distance(self):
rup = self._make_rupture(10, 15, 45) # 8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=0, sites=self.sitecol)
self.assertIsInstance(filtered, SiteCollection)
self.assertIsNot(filtered, self.sitecol)
numpy.testing.assert_array_equal(filtered.indices, [0])
numpy.testing.assert_array_equal(filtered.vs30, [0.1])
rup = self._make_rupture(50, 30, 90) # 14.8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=0, sites=self.sitecol)
numpy.testing.assert_array_equal(filtered.indices, [0, 1])
def test_495_km(self):
rup = self._make_rupture(5, 8, 5) # 4.68 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=495, sites=self.sitecol
)
numpy.testing.assert_array_equal(filtered.indices, [0, 1, 2, 3])
rup = self._make_rupture(7, 10, 30) # 5.8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=495, sites=self.sitecol
)
self.assertIs(filtered.indices, None)
self.assertIs(filtered, self.sitecol)
def test_zero_integration_distance(self):
rup = self._make_rupture(10, 15, 45) # 8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=0, sites=self.sitecol
)
self.assertIsInstance(filtered, SiteCollection)
self.assertIsNot(filtered, self.sitecol)
numpy.testing.assert_array_equal(filtered.indices, [0])
numpy.testing.assert_array_equal(filtered.vs30, [0.1])
rup = self._make_rupture(50, 30, 90) # 14.8 km radius
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=0, sites=self.sitecol
)
numpy.testing.assert_array_equal(filtered.indices, [0, 1])
def make_point_source(lon=1.2, lat=3.4, **kwargs):
default_arguments = {
'source_id': 'source_id',
'name': 'source name',
'tectonic_region_type': TRT.SUBDUCTION_INTRASLAB,
'mfd': TruncatedGRMFD(a_val=1,
b_val=2,
min_mag=3,
max_mag=5,
bin_width=1),
'location': Point(lon, lat, 5.6),
'nodal_plane_distribution': PMF([(1, NodalPlane(1, 2, 3))]),
'hypocenter_distribution': PMF([(1, 4)]),
'upper_seismogenic_depth': 1.3,
'lower_seismogenic_depth': 4.9,
'magnitude_scaling_relationship': PeerMSR(),
'rupture_aspect_ratio': 1.333,
'rupture_mesh_spacing': 1.234,
'temporal_occurrence_model': PoissonTOM(50.)
}
default_arguments.update(kwargs)
kwargs = default_arguments
ps = PointSource(**kwargs)
assert_pickleable(ps)
return ps
def test_filter_all_out(self):
rup = self._make_rupture(50, 80, 9) # 46.64 km radius
self.hypocenter.longitude = 11.515
for int_dist in (0, 1, 10, 100, 1000):
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=int_dist, sites=self.sitecol)
self.assertIs(filtered, None)
def __iter__(self):
for i, (mfd, point) in enumerate(zip(self.mfd, self.mesh)):
name = '%s:%s' % (self.source_id, i)
ps = PointSource(
name, name, self.tectonic_region_type,
mfd, self.rupture_mesh_spacing,
self.magnitude_scaling_relationship,
get(self.rupture_aspect_ratio, i),
self.temporal_occurrence_model,
get(self.upper_seismogenic_depth, i),
get(self.lower_seismogenic_depth, i),
point,
self.nodal_plane_distribution,
self.hypocenter_distribution)
ps.num_ruptures = ps.count_ruptures()
yield ps
def iter_ruptures(self):
"""
See :meth:
`openquake.hazardlib.source.base.BaseSeismicSource.iter_ruptures`
for description of parameters and return value.
Area sources are treated as a collection of point sources
(see :mod:`openquake.hazardlib.source.point`) with uniform parameters.
Ruptures of area source are just a union of ruptures
of those point sources. The actual positions of the implied
point sources form a uniformly spaced mesh on the polygon.
Polygon's method :meth:
`~openquake.hazardlib.geo.polygon.Polygon.discretize`
is used for creating a mesh of points on the source's area.
Constructor's parameter ``area_discretization`` is used as
polygon's discretization spacing (not to be confused with
rupture surface's mesh spacing which is as well provided
to the constructor).
The ruptures' occurrence rates are rescaled with respect to number
of points the polygon discretizes to.
"""
polygon_mesh = self.polygon.discretize(self.area_discretization)
rate_scaling_factor = 1.0 / len(polygon_mesh)
# take the very first point of the polygon mesh
[epicenter0] = polygon_mesh[0:1]
# generate "reference ruptures" -- all the ruptures that have the same
# epicenter location (first point of the polygon's mesh) but different
# magnitudes, nodal planes, hypocenters' depths and occurrence rates
# NB: all this mumbo-jumbo is done to avoid multiple calls to
# PointSource._get_rupture_surface
ref_ruptures = []
for mag, mag_occ_rate in self.get_annual_occurrence_rates():
for np_prob, np in self.nodal_plane_distribution.data:
for hc_prob, hc_depth in self.hypocenter_distribution.data:
hypocenter = geo.Point(latitude=epicenter0.latitude,
longitude=epicenter0.longitude,
depth=hc_depth)
occurrence_rate = (mag_occ_rate * np_prob * hc_prob *
rate_scaling_factor)
surface = PointSource._get_rupture_surface(
self, mag, np, hypocenter)
ref_ruptures.append(
(mag, np.rake, hc_depth, surface, occurrence_rate))
# for each of the epicenter positions generate as many ruptures
# as we generated "reference" ones: new ruptures differ only
# in hypocenter and surface location
for epicenter in polygon_mesh:
for mag, rake, hc_depth, surface, occ_rate in ref_ruptures:
# translate the surface from first epicenter position
# to the target one preserving it's geometry
surface = surface.translate(epicenter0, epicenter)
hypocenter = deepcopy(epicenter)
hypocenter.depth = hc_depth
rupture = ParametricProbabilisticRupture(
mag, rake, self.tectonic_region_type, hypocenter, surface,
occ_rate, self.temporal_occurrence_model)
yield rupture
def test_495_km(self):
rup = self._make_rupture(7, 10, 30)
# the JB distance area [5.84700762, 6.8290327, 14.53519629,
# 496.25926891, 497.37116174] so given that the integration
# distance is 495 only the first 3 sites are kept
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=495, sites=self.sitecol
)
expected_filtered = SiteCollection(self.SITES[:3])
numpy.testing.assert_array_equal(filtered.indices, [0, 1, 2])
numpy.testing.assert_array_equal(
filtered.vs30, expected_filtered.vs30
)
numpy.testing.assert_array_equal(
filtered.vs30measured, expected_filtered.vs30measured
)
numpy.testing.assert_array_equal(
filtered.z1pt0, expected_filtered.z1pt0
)
numpy.testing.assert_array_equal(
filtered.z2pt5, expected_filtered.z2pt5
)
numpy.testing.assert_array_equal(
filtered.mesh.lons, expected_filtered.mesh.lons
)
numpy.testing.assert_array_equal(
filtered.mesh.lats, expected_filtered.mesh.lats
)
numpy.testing.assert_array_equal(
filtered.mesh.depths, expected_filtered.mesh.depths
)
def polygon(self):
"""
The polygon containing all points expanded by the
max rupture projection radius
"""
maxradius = PointSource._get_max_rupture_projection_radius(self)
return self.mesh.get_convex_hull().dilate(maxradius)
def iter_ruptures(self):
"""
See :meth:
`openquake.hazardlib.source.base.BaseSeismicSource.iter_ruptures`
for description of parameters and return value.
Area sources are treated as a collection of point sources
(see :mod:`openquake.hazardlib.source.point`) with uniform parameters.
Ruptures of area source are just a union of ruptures
of those point sources. The actual positions of the implied
point sources form a uniformly spaced mesh on the polygon.
Polygon's method :meth:
`~openquake.hazardlib.geo.polygon.Polygon.discretize`
is used for creating a mesh of points on the source's area.
Constructor's parameter ``area_discretization`` is used as
polygon's discretization spacing (not to be confused with
rupture surface's mesh spacing which is as well provided
to the constructor).
The ruptures' occurrence rates are rescaled with respect to number
of points the polygon discretizes to.
"""
polygon_mesh = self.polygon.discretize(self.area_discretization)
rate_scaling_factor = 1.0 / len(polygon_mesh)
# take the very first point of the polygon mesh
[epicenter0] = polygon_mesh[0:1]
# generate "reference ruptures" -- all the ruptures that have the same
# epicenter location (first point of the polygon's mesh) but different
# magnitudes, nodal planes, hypocenters' depths and occurrence rates
# NB: all this mumbo-jumbo is done to avoid multiple calls to
# PointSource._get_rupture_surface
ref_ruptures = []
for mag, mag_occ_rate in self.get_annual_occurrence_rates():
for np_prob, np in self.nodal_plane_distribution.data:
for hc_prob, hc_depth in self.hypocenter_distribution.data:
hypocenter = geo.Point(latitude=epicenter0.latitude,
longitude=epicenter0.longitude,
depth=hc_depth)
occurrence_rate = (mag_occ_rate * np_prob * hc_prob
* rate_scaling_factor)
surface = PointSource._get_rupture_surface(
self, mag, np, hypocenter)
ref_ruptures.append((mag, np.rake, hc_depth,
surface, occurrence_rate))
# for each of the epicenter positions generate as many ruptures
# as we generated "reference" ones: new ruptures differ only
# in hypocenter and surface location
for epicenter in polygon_mesh:
for mag, rake, hc_depth, surface, occ_rate in ref_ruptures:
# translate the surface from first epicenter position
# to the target one preserving it's geometry
surface = surface.translate(epicenter0, epicenter)
hypocenter = deepcopy(epicenter)
hypocenter.depth = hc_depth
rupture = ParametricProbabilisticRupture(
mag, rake, self.tectonic_region_type, hypocenter,
surface, occ_rate, self.temporal_occurrence_model)
yield rupture
def test_filter_all_out(self):
rup = self._make_rupture(50, 80, 9) # 46.64 km radius
self.hypocenter.longitude = 11.515
for int_dist in (0, 1, 10, 100, 1000):
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=int_dist, sites=self.sitecol
)
self.assertIs(filtered, None)
def test_rupture_close_to_south_pole(self):
# data taken from real example and causing "surface's angles are not
# right" error
mfd = EvenlyDiscretizedMFD(
min_mag=5., bin_width=0.1, occurrence_rates=[2.180e-07]
)
nodal_plane_dist = PMF([(1., NodalPlane(135., 20., 90.))])
src = PointSource(source_id='1', name='pnt', tectonic_region_type='asc',
mfd=mfd, rupture_mesh_spacing=1,
magnitude_scaling_relationship=WC1994(),
rupture_aspect_ratio=1.,
upper_seismogenic_depth=0, lower_seismogenic_depth=26,
location=Point(-165.125, -83.600),
nodal_plane_distribution=nodal_plane_dist,
hypocenter_distribution=PMF([(1., 9.)]))
ruptures = list(src.iter_ruptures(PoissonTOM(50.)))
self.assertEqual(len(ruptures), 1)
def test_rupture_close_to_south_pole(self):
# data taken from real example and causing "surface's angles are not
# right" error
mfd = EvenlyDiscretizedMFD(
min_mag=5., bin_width=0.1, occurrence_rates=[2.180e-07]
)
nodal_plane_dist = PMF([(1., NodalPlane(135., 20., 90.))])
src = PointSource(source_id='1', name='pnt', tectonic_region_type='asc',
mfd=mfd, rupture_mesh_spacing=1,
magnitude_scaling_relationship=WC1994(),
rupture_aspect_ratio=1.,
temporal_occurrence_model=PoissonTOM(50.),
upper_seismogenic_depth=0, lower_seismogenic_depth=26,
location=Point(-165.125, -83.600),
nodal_plane_distribution=nodal_plane_dist,
hypocenter_distribution=PMF([(1., 9.)]))
ruptures = list(src.iter_ruptures())
self.assertEqual(len(ruptures), 1)
def test_zero_integration_distance(self):
rup = self._make_rupture(10, 15, 45)
# the JB distances are [8.29156163, 5.05971598, 15.13297135,
# 495.78630103, 496.89812309], so given that the integration
# distance is 0 all sites are filtered out
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=0, sites=self.sitecol
)
self.assertIs(filtered, None)
def test_filter_all_out(self):
rup = self._make_rupture(50, 80, 9)
# the JB distances are [47.0074159, 37.99716685, 40.7944923,
# 476.2521365, 477.36015879]
for int_dist in (0, 1, 10, 20, 37.99):
filtered = PointSource.filter_sites_by_distance_to_rupture(
rup, integration_distance=int_dist, sites=self.sitecol
)
self.assertIs(filtered, None)
def get_background_sources(self, src_filter, sample_factor=None):
"""
Turn the background model of a given branch into a set of point sources
:param src_filter:
SourceFilter instance
:param sample_factor:
Used to reduce the sources if OQ_SAMPLE_SOURCES is set
"""
background_sids = self.get_background_sids(src_filter)
if sample_factor is not None: # hack for use in the mosaic
background_sids = random_filter(
background_sids, sample_factor, seed=42)
with h5py.File(self.source_file, "r") as hdf5:
grid_loc = "/".join(["Grid", self.idx_set["grid_key"]])
# for instance Grid/FM0_0_MEANFS_MEANMSR_MeanRates
mags = hdf5[grid_loc + "/Magnitude"].value
mmax = hdf5[grid_loc + "/MMax"][background_sids]
rates = hdf5[grid_loc + "/RateArray"][background_sids, :]
locations = hdf5["Grid/Locations"][background_sids, :]
sources = []
for i, bg_idx in enumerate(background_sids):
src_id = "_".join([self.idx_set["grid_key"], str(bg_idx)])
src_name = "|".join([self.idx_set["total_key"], str(bg_idx)])
mag_idx = (self.min_mag <= mags) & (mags < mmax[i])
src_mags = mags[mag_idx]
src_mfd = EvenlyDiscretizedMFD(
src_mags[0],
src_mags[1] - src_mags[0],
rates[i, mag_idx].tolist())
ps = PointSource(
src_id, src_name, self.tectonic_region_type, src_mfd,
self.mesh_spacing, self.msr, self.aspect, self.tom,
self.usd, self.lsd,
Point(locations[i, 0], locations[i, 1]),
self.npd, self.hdd)
ps.id = self.id
ps.src_group_id = self.src_group_id
ps.num_ruptures = ps.count_ruptures()
sources.append(ps)
return sources
def get_background_sources(self, sample_factor=None):
"""
Turn the background model of a given branch into a set of point sources
:param sample_factor:
Used to reduce the sources if OQ_SAMPLE_SOURCES is set
"""
background_sids = self.get_background_sids()
if sample_factor is not None: # hack for use in the mosaic
background_sids = random_filter(
background_sids, sample_factor, seed=42)
with h5py.File(self.source_file, "r") as hdf5:
grid_loc = "/".join(["Grid", self.idx_set["grid_key"]])
# for instance Grid/FM0_0_MEANFS_MEANMSR_MeanRates
mags = hdf5[grid_loc + "/Magnitude"][()]
mmax = hdf5[grid_loc + "/MMax"][background_sids]
rates = hdf5[grid_loc + "/RateArray"][background_sids, :]
locations = hdf5["Grid/Locations"][background_sids, :]
sources = []
for i, bg_idx in enumerate(background_sids):
src_id = "_".join([self.idx_set["grid_key"], str(bg_idx)])
src_name = "|".join([self.idx_set["total_key"], str(bg_idx)])
mag_idx = (self.min_mag <= mags) & (mags < mmax[i])
src_mags = mags[mag_idx]
src_mfd = EvenlyDiscretizedMFD(
src_mags[0],
src_mags[1] - src_mags[0],
rates[i, mag_idx].tolist())
ps = PointSource(
src_id, src_name, self.tectonic_region_type, src_mfd,
self.mesh_spacing, self.msr, self.aspect, self.tom,
self.usd, self.lsd,
Point(locations[i, 0], locations[i, 1]),
self.npd, self.hdd)
ps.checksum = zlib.adler32(pickle.dumps(vars(ps), protocol=4))
ps._wkt = ps.wkt()
ps.id = self.id
ps.grp_id = self.grp_id
ps.num_ruptures = ps.count_ruptures()
sources.append(ps)
return sources
def create_oqhazardlib_source(self, tom, mesh_spacing, use_defaults=False):
"""
Converts the point source model into an instance of the :class:
openquake.hazardlib.source.point_source.PointSource
:param bool use_defaults:
If set to true, will use put in default values for magitude
scaling relation, rupture aspect ratio, nodal plane distribution
or hypocentral depth distribution where missing. If set to False
then value errors will be raised when information is missing.
"""
return PointSource(
self.id, self.name, self.trt, conv.mfd_to_hazardlib(self.mfd),
mesh_spacing,
conv.mag_scale_rel_to_hazardlib(self.mag_scale_rel, use_defaults),
conv.render_aspect_ratio(self.rupt_aspect_ratio, use_defaults),
tom, self.upper_depth, self.lower_depth, self.geometry,
conv.npd_to_pmf(self.nodal_plane_dist, use_defaults),
conv.hdd_to_pmf(self.hypo_depth_dist, use_defaults))
def test(self):
sitecol = SiteCollection([Site(Point(30.0, 30.0), 760., 1.0, 1.0)])
mfd = TruncatedGRMFD(4.5, 8.0, 0.1, 4.0, 1.0)
sources = [
PointSource('001', 'Point1', 'Active Shallow Crust', mfd, 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)]))
]
imtls = {'PGA': [0.01, 0.1, 0.2, 0.5, 0.8]}
hc1 = calc_hazard_curves(
sources, sitecol, imtls,
{'Active Shallow Crust': AkkarBommer2010()})['PGA']
hc2 = calc_hazard_curves(
sources, sitecol, imtls,
{'Active Shallow Crust': SadighEtAl1997()})['PGA']
hc = .6 * hc1 + .4 * hc2
ag = AvgGMPE(b1=dict(AkkarBommer2010={'weight': .6}),
b2=dict(SadighEtAl1997={'weight': .4}))
hcm = calc_hazard_curves(sources, sitecol, imtls,
{'Active Shallow Crust': ag})['PGA']
# the AvgGMPE is not producing real means!!
numpy.testing.assert_almost_equal(hc, hcm, decimal=3)
def run_smoothing(grid_lims, config, catalogue, completeness_table, map_config,
run):
"""Run all the smoothing
:params config:
Dictionary of configuration parameters.
For more info see helmstetter_werner_2012 code
and docs.
"""
completeness_string = 'comp'
for ym in completeness_table:
completeness_string += '_%i_%.1f' % (ym[0], ym[1])
smoother_filename = "Australia_Adaptive_K%i_b%.3f_mmin%.1f_%s.csv" % (
config['k'], config['bvalue'], config['mmin'], completeness_string)
filename = smoother_filename[:-4] + '.xml'
if os.path.exists(filename) and not overwrite:
print '%s already created, not overwriting!' % filename
return
smoother = h_w.HelmstetterEtAl2007(grid_lims,
config,
catalogue,
storage_file=("Aus1_tmp2%.3f_%s.hdf5" %
(config['bvalue'], run)))
smoother._get_catalogue_completeness_weights(completeness_table)
smoother.build_distance_arrays()
smoother.build_catalogue_2_grid_array()
# Exhaustive smoothing
exhaustive = False
if exhaustive == True:
params, poiss_llh = smoother.exhaustive_smoothing(
np.arange(2, 10, 1), np.arange(1.0e-6, 1.0e-5, 2.0e-6))
print params, poiss_llh
smoother.config["k"] = params[0]
smoother.config["r_min"] = params[1]
#print 'Exiting now, re-run using optimised parameters'
#sys.exit()
d_i = smoother.optimise_bandwidths()
smoother.run_smoothing(config["r_min"], d_i)
data = np.column_stack([smoother.grid, smoother.rates])
np.savetxt(
smoother_filename,
data,
# np.column_stack([smoother.grid, smoother.rates]),
delimiter=",",
fmt=["%.4f", "%.4f", "%.8e"],
header="longitude,latitude,rate")
# Creating a basemap - input a cconfiguration and (if desired) a title
title = 'Smoothed seismicity rate for learning \nperiod %i %i, K=%i, Mmin=%.1f' % (
config['learning_start'], config['learning_end'], smoother.config['k'],
smoother.config['mmin'])
basemap1 = HMTKBaseMap(map_config, title)
basemap1.m.drawmeridians(
np.arange(map_config['min_lat'], map_config['max_lat'], 5))
basemap1.m.drawparallels(
np.arange(map_config['min_lon'], map_config['max_lon'], 5))
# Adding the smoothed grip to the basemap
sym = (2., 3., 'cx')
x, y = basemap1.m(smoother.grid[:, 0], smoother.grid[:, 1])
if smoother.config['mmin'] == 3.5:
vmax = -1.0
elif smoother.config['mmin'] == 4.0:
vmax = -2.5
else:
vmax = -1.0
basemap1.m.scatter(x,
y,
marker='s',
c=np.log10(smoother.rates),
cmap=plt.cm.coolwarm,
zorder=10,
lw=0,
vmin=-7.0,
vmax=vmax)
basemap1.m.drawcoastlines(linewidth=1, zorder=50) # Add coastline on top
#basemap1.m.drawmeridians(np.arange(llat, ulat, 5))
#basemap1.m.drawparallels(np.arange(llon, ulon, 5))
plt.colorbar(label='Log10(Smoothed rate per cell)')
#plt.colorbar()#label='log10(Smoothed rate per cell)')
plt.legend()
#basemap1.m.scatter(x, y, marker = 's', c = smoother.data[:,4], cmap = plt.cm.coolwarm, zorder=10)
#basemap1.m.scatter([150],[22], marker='o')
#basemap1.fig.show()
#(smoother.data[0], smoother.data[1])
#basemap1.add_catalogue(catalogue_depth_clean, erlay=False)
figname = smoother_filename[:-4] + '_smoothed_rates_map.png'
plt.savefig(figname)
source_list = []
#i=0
min_mag = 4.5
max_mag = 7.2
# Read in data again to solve number fomatting issue in smoother.data
# For some reason it just returns 0 for all a values
#data = np.genfromtxt(smoother_filename, delimiter = ',', skip_header = 1)
tom = PoissonTOM(
50) # Dummy temporal occurence model for building pt sources
msr = Leonard2014_SCR()
for j in range(len(data[:, 2])):
identifier = 'ASS' + str(j) + '_' + str(run)
name = 'Helmstetter' + str(j) + '_' + str(run)
point = Point(data[j, 0], data[j, 1], 10)
rate = data[j, 2]
# Convert rate to a value
aval = np.log10(rate) + config['bvalue'] * config["mmin"]
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, config['bvalue'])
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
(0.2, NodalPlane(270, 30, 90))])
point_source = PointSource(identifier, name, 'Non_cratonic', mfd, 2,
msr, 2.0, tom, 0.1, 20.0, point,
nodal_plane_dist, hypo_depth_dist)
source_list.append(point_source)
mod_name = "Australia_Adaptive_K%i_b%.3f" % (smoother.config['k'],
smoother.config['bvalue'])
nodes = list(map(obj_to_node, sorted(source_list)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(filename, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
nodal_plane_distribution = nodal_plane_dist # FIXME! update based on data extracted from shapefile
hypocenter_distribution = hypo_depth_dist
rupture_aspect_ratio = 2
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, a_values[i],
b_values[i])
new_mfd = gr2inc_mmax(mfd,
mmaxs[dom['CODE']],
mmaxs_w[dom['CODE']],
model_weight=1.)
mfd = new_mfd
name = 'Hall_%i' % ids[i]
source_id = name
if source_id in pt_ids:
print 'Point source %s already exists!' % source_id
print 'Skipping this source for trt %s' % dom['TRT']
else:
pt_source = PointSource(source_id, name,
dom['GMM_TRT'], mfd, 2, msr,
1.5, tom, 0.1, 20.0, pt,
nodal_plane_dist,
hypo_depth_dist)
merged_pts.append(pt_source)
pt_ids.append(source_id)
outfile = 'Hall2007_2018.xml'
name = outfile.rstrip('.xml')
if nrml_version == '04':
nodes = list(map(obj_to_node, sorted(merged_pts)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(outfile, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
identifier = 'FSS' + str(j)
name = 'Frankel' + str(j)
point = Point(data[j, 0], data[j, 1], data[j, 2])
rate = data[j, 4]
aval = np.log10(rate)
# aval = rate # trying this based on some testing
# aval = np.log10(rate) #+ bval*completeness_table_a[0][1]
# print aval
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, bval)
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
(0.2, NodalPlane(270, 30, 90))])
point_source = PointSource(identifier, name, 'Non_cratonic', mfd, 2, msr,
2.0, tom, 0.1, 20.0, point, nodal_plane_dist,
hypo_depth_dist)
source_list.append(point_source)
# i+=1
# if j==1000:
# break
filename = "smoothed_frankel_50_3_mmin_%.1f_b%.3f_0.1.xml" % (
completeness_table_a[0][-1], bvalue)
mod_name = 'smoothed_frankel_50_3_mmin_%.1f_b%.3f_0.1' % (
completeness_table_a[0][-1], bvalue)
nodes = list(map(obj_to_node, sorted(source_list)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(filename, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
def test_7_many_ruptures(self):
source_id = name = 'test7-source'
trt = TRT.VOLCANIC
mag1 = 4.5
mag2 = 5.5
mag1_rate = 9e-3
mag2_rate = 9e-4
hypocenter1 = 9.0
hypocenter2 = 10.0
hypocenter1_weight = Decimal('0.8')
hypocenter2_weight = Decimal('0.2')
nodalplane1 = NodalPlane(strike=45, dip=90, rake=0)
nodalplane2 = NodalPlane(strike=0, dip=45, rake=10)
nodalplane1_weight = Decimal('0.3')
nodalplane2_weight = Decimal('0.7')
upper_seismogenic_depth = 2
lower_seismogenic_depth = 16
rupture_aspect_ratio = 2
rupture_mesh_spacing = 0.5
location = Point(0, 0)
magnitude_scaling_relationship = PeerMSR()
tom = PoissonTOM(time_span=50)
mfd = EvenlyDiscretizedMFD(min_mag=mag1, bin_width=(mag2 - mag1),
occurrence_rates=[mag1_rate, mag2_rate])
nodal_plane_distribution = PMF([(nodalplane1_weight, nodalplane1),
(nodalplane2_weight, nodalplane2)])
hypocenter_distribution = PMF([(hypocenter1_weight, hypocenter1),
(hypocenter2_weight, hypocenter2)])
point_source = PointSource(
source_id, name, trt, mfd, rupture_mesh_spacing,
magnitude_scaling_relationship, rupture_aspect_ratio,
upper_seismogenic_depth, lower_seismogenic_depth,
location, nodal_plane_distribution, hypocenter_distribution
)
actual_ruptures = list(point_source.iter_ruptures(tom))
self.assertEqual(len(actual_ruptures), 8)
expected_ruptures = {
(mag1, nodalplane1.rake, hypocenter1): (
# probabilistic rupture's occurrence rate
9e-3 * 0.3 * 0.8,
# rupture surface corners
planar_surface_test_data.TEST_7_RUPTURE_1_CORNERS
),
(mag2, nodalplane1.rake, hypocenter1): (
9e-4 * 0.3 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_2_CORNERS
),
(mag1, nodalplane2.rake, hypocenter1): (
9e-3 * 0.7 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_3_CORNERS
),
(mag2, nodalplane2.rake, hypocenter1): (
9e-4 * 0.7 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_4_CORNERS
),
(mag1, nodalplane1.rake, hypocenter2): (
9e-3 * 0.3 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_5_CORNERS
),
(mag2, nodalplane1.rake, hypocenter2): (
9e-4 * 0.3 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_6_CORNERS
),
(mag1, nodalplane2.rake, hypocenter2): (
9e-3 * 0.7 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_7_CORNERS
),
(mag2, nodalplane2.rake, hypocenter2): (
9e-4 * 0.7 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_8_CORNERS
)
}
for actual_rupture in actual_ruptures:
expected_occurrence_rate, expected_corners = expected_ruptures[
(actual_rupture.mag, actual_rupture.rake,
actual_rupture.hypocenter.depth)
]
self.assertTrue(isinstance(actual_rupture, ProbabilisticRupture))
self.assertEqual(actual_rupture.occurrence_rate,
expected_occurrence_rate)
self.assertIs(actual_rupture.temporal_occurrence_model, tom)
self.assertEqual(actual_rupture.tectonic_region_type, trt)
surface = actual_rupture.surface
tl, tr, br, bl = expected_corners
self.assertEqual(tl, surface.top_left)
self.assertEqual(tr, surface.top_right)
self.assertEqual(bl, surface.bottom_left)
self.assertEqual(br, surface.bottom_right)
def run_smoothing(grid_lims,
smoothing_config,
catalogue,
completeness_table,
map_config,
run,
overwrite=True):
"""Run all the smoothing
"""
ystart = completeness_table[-1][0]
yend = catalogue.end_year
catalogue_comp = deepcopy(catalogue)
# Ensuring that catalogue is cleaned of earthquakes outside of
# completeness period
index = catalogue_comp.data['year'] >= ystart
catalogue_comp.purge_catalogue(index)
completeness_string = 'comp'
for ym in completeness_table:
completeness_string += '_%i_%.1f' % (ym[0], ym[1])
smoother_filename = 'Australia_Fixed_%i_%i_b%.3f_mmin_%.1f_0.1%s.csv' % (
smoothing_config["BandWidth"], smoothing_config["Length_Limit"],
bvalue, completeness_table[0][1], completeness_string)
filename = smoother_filename[:-4] + '.xml'
if os.path.exists(filename) and not overwrite:
print '%s already created, not overwriting!' % filename
return
smoother = SmoothedSeismicity(
[105., 160., 0.1, -47., -5, 0.1, 0., 20., 20.],
bvalue=smoothing_config['bvalue'])
print 'Running smoothing'
smoothed_grid = smoother.run_analysis(
catalogue_comp,
smoothing_config,
completeness_table=completeness_table)
smoother.write_to_csv(smoother_filename)
from openquake.hazardlib.nrml import SourceModelParser, write, NAMESPACE
from openquake.baselib.node import Node
from openquake.hazardlib import nrml
from openquake.hazardlib.sourcewriter import obj_to_node
# Build nrml input file of point sources
source_list = []
#i=0
min_mag = 4.5
max_mag = 7.8
bval = bvalue # just define as 1 for time being
# Read in data again to solve number fomatting issue in smoother.data
# For some reason it just returns 0 for all a values
try:
data = np.genfromtxt(smoother_filename, delimiter=',', skip_header=1)
except ValueError:
print 'Something wrong with file %s' % smoother_filename
sys.exit()
tom = PoissonTOM(
50) # Dummy temporal occurence model for building pt sources
msr = Leonard2014_SCR()
for j in range(len(data[:, 4])):
# print smoother.data[j,:]
identifier = 'FSS' + str(j) + '_' + str(run)
name = 'Frankel' + str(j) + '_' + str(run)
point = Point(data[j, 0], data[j, 1], data[j, 2])
annual_rate = data[j, 4] / (yend - ystart + 1)
aval = np.log10(annual_rate) + smoothing_config[
'bvalue'] * completeness_table[0][1]
mfd = TruncatedGRMFD(min_mag, max_mag, 0.1, aval, bval)
hypo_depth_dist = PMF([(0.5, 10.0), (0.25, 5.0), (0.25, 15.0)])
nodal_plane_dist = PMF([(0.3, NodalPlane(0, 30, 90)),
(0.2, NodalPlane(90, 30, 90)),
(0.3, NodalPlane(180, 30, 90)),
(0.2, NodalPlane(270, 30, 90))])
point_source = PointSource(identifier, name, 'Non_cratonic', mfd, 2,
msr, 2.0, tom, 0.1, 20.0, point,
nodal_plane_dist, hypo_depth_dist)
source_list.append(point_source)
nodes = list(map(obj_to_node, sorted(source_list)))
source_model = Node("sourceModel", {"name": name}, nodes=nodes)
with open(filename, 'wb') as f:
nrml.write([source_model], f, '%s', xmlns=NAMESPACE)
# Creating a basemap - input a cconfiguration and (if desired) a title
title = 'Smoothed seismicity rate for learning \nperiod %i 2017, Mmin = %.1f' % (
completeness_table[0][0], completeness_table[0][1])
basemap1 = HMTKBaseMap(map_config, 'Smoothed seismicity rate')
# Adding the smoothed grip to the basemap
sym = (2., 3., 'cx')
x, y = basemap1.m(smoother.data[:, 0], smoother.data[:, 1])
basemap1.m.scatter(x,
y,
marker='s',
c=np.log10(smoother.data[:, 4]),
cmap=plt.cm.coolwarm,
zorder=10,
lw=0,
vmin=-6.5,
vmax=1.5)
basemap1.m.drawcoastlines(linewidth=1, zorder=50) # Add coastline on top
basemap1.m.drawmeridians(
np.arange(map_config['min_lat'], map_config['max_lat'], 5))
basemap1.m.drawparallels(
np.arange(map_config['min_lon'], map_config['max_lon'], 5))
plt.colorbar(label='log10(Smoothed rate per cell)')
plt.legend()
figname = smoother_filename[:-4] + '_smoothed_rates_map.png'
plt.savefig(figname)
from openquake.hazardlib.geo.line import Line
from openquake.hazardlib.scalerel.point import PointMSR
from openquake.hazardlib.scalerel.peer import PeerMSR
from openquake.hazardlib.tom import PoissonTOM
from openquake.hazardlib.geo.surface.simple_fault import SimpleFaultSurface
from openquake.hmtk.comparison.rate_grids import RateGrid, RatePolygon
SOURCE_MODEL_FILE = os.path.join(os.path.dirname(__file__),
"rate_grid_test_model.xml")
POINT_SOURCE = PointSource("PNT000", "Point 000",
"Active Shallow Crust",
EvenlyDiscretizedMFD(5.0, 0.1, [1.0]),
1.0,
PointMSR(),
1.0,
PoissonTOM(1.0),
0.0,
20.0,
Point(15.05, 15.05),
PMF([(1.0, NodalPlane(0.0, 90.0, 0.0))]),
PMF([(1.0, 5.0)]))
BORDER_POINT_SOURCE = PointSource("PNT000", "Point 000",
"Active Shallow Crust",
EvenlyDiscretizedMFD(5.0, 0.1, [1.0]),
1.0,
PointMSR(),
1.0,
PoissonTOM(1.0),
0.0,
20.0,
def test_7_many_ruptures(self):
source_id = name = 'test7-source'
trt = TRT.VOLCANIC
mag1 = 4.5
mag2 = 5.5
mag1_rate = 9e-3
mag2_rate = 9e-4
hypocenter1 = 9.0
hypocenter2 = 10.0
hypocenter1_weight = Decimal('0.8')
hypocenter2_weight = Decimal('0.2')
nodalplane1 = NodalPlane(strike=45, dip=90, rake=0)
nodalplane2 = NodalPlane(strike=0, dip=45, rake=10)
nodalplane1_weight = Decimal('0.3')
nodalplane2_weight = Decimal('0.7')
upper_seismogenic_depth = 2
lower_seismogenic_depth = 16
rupture_aspect_ratio = 2
rupture_mesh_spacing = 0.5
location = Point(0, 0)
magnitude_scaling_relationship = PeerMSR()
tom = PoissonTOM(time_span=50)
mfd = EvenlyDiscretizedMFD(min_mag=mag1,
bin_width=(mag2 - mag1),
occurrence_rates=[mag1_rate, mag2_rate])
nodal_plane_distribution = PMF([(nodalplane1_weight, nodalplane1),
(nodalplane2_weight, nodalplane2)])
hypocenter_distribution = PMF([(hypocenter1_weight, hypocenter1),
(hypocenter2_weight, hypocenter2)])
point_source = PointSource(
source_id, name, trt, mfd, rupture_mesh_spacing,
magnitude_scaling_relationship, rupture_aspect_ratio, tom,
upper_seismogenic_depth, lower_seismogenic_depth, location,
nodal_plane_distribution, hypocenter_distribution)
actual_ruptures = list(point_source.iter_ruptures())
self.assertEqual(len(actual_ruptures), point_source.count_ruptures())
expected_ruptures = {
(mag1, nodalplane1.rake, hypocenter1): (
# probabilistic rupture's occurrence rate
9e-3 * 0.3 * 0.8,
# rupture surface corners
planar_surface_test_data.TEST_7_RUPTURE_1_CORNERS),
(mag2, nodalplane1.rake, hypocenter1):
(9e-4 * 0.3 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_2_CORNERS),
(mag1, nodalplane2.rake, hypocenter1):
(9e-3 * 0.7 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_3_CORNERS),
(mag2, nodalplane2.rake, hypocenter1):
(9e-4 * 0.7 * 0.8,
planar_surface_test_data.TEST_7_RUPTURE_4_CORNERS),
(mag1, nodalplane1.rake, hypocenter2):
(9e-3 * 0.3 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_5_CORNERS),
(mag2, nodalplane1.rake, hypocenter2):
(9e-4 * 0.3 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_6_CORNERS),
(mag1, nodalplane2.rake, hypocenter2):
(9e-3 * 0.7 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_7_CORNERS),
(mag2, nodalplane2.rake, hypocenter2):
(9e-4 * 0.7 * 0.2,
planar_surface_test_data.TEST_7_RUPTURE_8_CORNERS)
}
for actual_rupture in actual_ruptures:
expected_occurrence_rate, expected_corners = expected_ruptures[(
actual_rupture.mag, actual_rupture.rake,
actual_rupture.hypocenter.depth)]
self.assertTrue(
isinstance(actual_rupture, ParametricProbabilisticRupture))
self.assertEqual(actual_rupture.occurrence_rate,
expected_occurrence_rate)
self.assertIs(actual_rupture.temporal_occurrence_model, tom)
self.assertEqual(actual_rupture.tectonic_region_type, trt)
surface = actual_rupture.surface
tl, tr, br, bl = expected_corners
self.assertEqual(tl, surface.top_left)
self.assertEqual(tr, surface.top_right)
self.assertEqual(bl, surface.bottom_left)
self.assertEqual(br, surface.bottom_right)
