def test_source_errors(self):
# exercise the case where an error occurs while computing on a given
# seismic source; in this case, we expect an error to be raised which
# signals the id of the source in question
fail_source = self.FailSource(self.source2.source_id,
self.source2.ruptures, self.source2.tom,
self.source2.tectonic_region_type)
sources = iter([self.source1, fail_source])
with self.assertRaises(RuntimeError) as ae:
bin_edges, matrix = disagg.disaggregation_poissonian(
sources,
self.site,
self.imt,
self.iml,
self.gsims,
self.time_span,
self.truncation_level,
n_epsilons=3,
mag_bin_width=3,
dist_bin_width=4,
coord_bin_width=2.4)
expected_error = (
'An error occurred with source id=2. Error: Something bad happened'
)
self.assertEqual(expected_error, ae.exception.message)
def test(self):
self.gsim.truncation_level = self.truncation_level = 1
bin_edges, matrix = disagg.disaggregation_poissonian(
self.sources, self.site, self.imt, self.iml, self.gsims,
self.time_span, self.truncation_level, n_epsilons=3,
mag_bin_width=3, dist_bin_width=4, coord_bin_width=2.4
)
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins, trt_bins = bin_edges
aaae = numpy.testing.assert_array_almost_equal
aaae(mag_bins, [3, 6, 9])
aaae(dist_bins, [0, 4, 8, 12, 16])
aaae(lon_bins, [9.6, 12., 14.4, 16.8, 19.2, 21.6, 24.])
aaae(lat_bins, [43.2, 45.6, 48.])
aaae(eps_bins, [-1, -0.3333333, 0.3333333, 1])
self.assertEqual(trt_bins, ['trt1', 'trt2'])
for idx, value in [((0, 2, 4, 0, 0, 0), 0.0429088739427),
((0, 2, 4, 0, 1, 0), 0.0915231841771),
((0, 2, 4, 0, 2, 0), 0.0539109573863),
((0, 2, 5, 0, 0, 0), 0.0524944739774),
((0, 2, 5, 0, 1, 0), 0.0831147185105),
((0, 2, 5, 0, 2, 0), 0.0553469961235),
((0, 3, 5, 0, 1, 0), 0.0198247319211),
((0, 3, 5, 0, 2, 0), 0.00040039738616),
((1, 1, 0, 0, 1, 1), 0.00407387860215),
((1, 1, 0, 0, 2, 1), 0.00163154735795),
((1, 1, 0, 1, 0, 1), 0.00304128663811),
((1, 1, 0, 1, 1, 1), 0.0151142198204),
((1, 1, 0, 1, 2, 1), 0.00304128663811)]:
self.assertAlmostEqual(matrix[idx], value)
matrix[idx] = 0
self.assertEqual(matrix.sum(), 0)
def test_no_contributions_from_ruptures(self):
# Test that the `disaggregation` function returns `None, None` if no
# ruptures contribute to the hazard level.
array = numpy.array
float64 = numpy.float64
int64 = numpy.int64
# This is the result we get if the sources produce no ruptures:
fake_bins_data = (array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=int64), [])
with mock.patch(
'openquake.hazardlib.calc.disagg._collect_bins_data') as cbd:
with warnings.catch_warnings(record=True) as w:
cbd.return_value = fake_bins_data
self.gsim.truncation_level = self.truncation_level = 1
bin_edges, matrix = disagg.disaggregation_poissonian(
self.sources,
self.site,
self.imt,
self.iml,
self.gsims,
self.time_span,
self.truncation_level,
n_epsilons=3,
mag_bin_width=3,
dist_bin_width=4,
coord_bin_width=2.4,
)
# We expect to get back 2 `None` values:
self.assertIsNone(bin_edges)
self.assertIsNone(matrix)
# Also check for the warning that should be raised:
expected_warning_msg = (
'No ruptures have contributed to the hazard at site '
'<Location=<Latitude=0.000000, Longitude=0.000000, '
'Depth=0.0000>, Vs30=2.0000, Vs30Measured=False, '
'Depth1.0km=4.0000, Depth2.5km=5.0000>')
self.assertEqual(1, len(w))
[warning] = list(w)
self.assertEqual(expected_warning_msg, warning.message.message)
def test_source_errors(self):
# exercise the case where an error occurs while computing on a given
# seismic source; in this case, we expect an error to be raised which
# signals the id of the source in question
fail_source = self.FailSource(self.source2.source_id,
self.source2.ruptures,
self.source2.tom,
self.source2.tectonic_region_type)
sources = iter([self.source1, fail_source])
with self.assertRaises(RuntimeError) as ae:
bin_edges, matrix = disagg.disaggregation_poissonian(
sources, self.site, self.imt, self.iml, self.gsims,
self.time_span, self.truncation_level, n_epsilons=3,
mag_bin_width=3, dist_bin_width=4, coord_bin_width=2.4
)
expected_error = (
'An error occurred with source id=2. Error: Something bad happened'
)
self.assertEqual(expected_error, ae.exception.message)
def test(self):
self.gsim.truncation_level = self.truncation_level = 1
bin_edges, matrix = disagg.disaggregation_poissonian(
self.sources,
self.site,
self.imt,
self.iml,
self.gsims,
self.time_span,
self.truncation_level,
n_epsilons=3,
mag_bin_width=3,
dist_bin_width=4,
coord_bin_width=2.4)
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins, trt_bins = bin_edges
aaae = numpy.testing.assert_array_almost_equal
aaae(mag_bins, [3, 6, 9])
aaae(dist_bins, [0, 4, 8, 12, 16])
aaae(lon_bins, [9.6, 12., 14.4, 16.8, 19.2, 21.6, 24.])
aaae(lat_bins, [43.2, 45.6, 48.])
aaae(eps_bins, [-1, -0.3333333, 0.3333333, 1])
self.assertEqual(trt_bins, ['trt1', 'trt2'])
for idx, value in [((0, 2, 4, 0, 0, 0), 0.0429088739427),
((0, 2, 4, 0, 1, 0), 0.0915231841771),
((0, 2, 4, 0, 2, 0), 0.0539109573863),
((0, 2, 5, 0, 0, 0), 0.0524944739774),
((0, 2, 5, 0, 1, 0), 0.0831147185105),
((0, 2, 5, 0, 2, 0), 0.0553469961235),
((0, 3, 5, 0, 1, 0), 0.0198247319211),
((0, 3, 5, 0, 2, 0), 0.00040039738616),
((1, 1, 0, 0, 1, 1), 0.00407387860215),
((1, 1, 0, 0, 2, 1), 0.00163154735795),
((1, 1, 0, 1, 0, 1), 0.00304128663811),
((1, 1, 0, 1, 1, 1), 0.0151142198204),
((1, 1, 0, 1, 2, 1), 0.00304128663811)]:
self.assertAlmostEqual(matrix[idx], value)
matrix[idx] = 0
self.assertEqual(matrix.sum(), 0)
def test_no_contributions_from_ruptures(self):
# Test that the `disaggregation` function returns `None, None` if no
# ruptures contribute to the hazard level.
array = numpy.array
float64 = numpy.float64
int64 = numpy.int64
# This is the result we get if the sources produce no ruptures:
fake_bins_data = (array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=int64), [])
with mock.patch(
'openquake.hazardlib.calc.disagg._collect_bins_data'
) as cbd:
with warnings.catch_warnings(record=True) as w:
cbd.return_value = fake_bins_data
self.gsim.truncation_level = self.truncation_level = 1
bin_edges, matrix = disagg.disaggregation_poissonian(
self.sources, self.site, self.imt, self.iml, self.gsims,
self.time_span, self.truncation_level, n_epsilons=3,
mag_bin_width=3, dist_bin_width=4, coord_bin_width=2.4,
)
# We expect to get back 2 `None` values:
self.assertIsNone(bin_edges)
self.assertIsNone(matrix)
# Also check for the warning that should be raised:
expected_warning_msg = (
'No ruptures have contributed to the hazard at site '
'<Location=<Latitude=0.000000, Longitude=0.000000, '
'Depth=0.0000>, Vs30=2.0000, Vs30Measured=False, '
'Depth1.0km=4.0000, Depth2.5km=5.0000>'
)
self.assertEqual(1, len(w))
[warning] = list(w)
self.assertEqual(expected_warning_msg, warning.message.message)
def test_areasource(self):
nodalplane = NodalPlane(strike=0.0, dip=90.0, rake=0.0)
src = AreaSource(
source_id='src_1',
name='area source',
tectonic_region_type='Active Shallow Crust',
mfd=TruncatedGRMFD(a_val=3.5, b_val=1.0, min_mag=5.0,
max_mag=6.5, bin_width=0.1),
nodal_plane_distribution=PMF([(1.0, nodalplane)]),
hypocenter_distribution=PMF([(1.0, 5.0)]),
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=10.0,
magnitude_scaling_relationship = WC1994(),
rupture_aspect_ratio=1.0,
polygon=Polygon([Point(-0.5,-0.5), Point(-0.5,0.5),
Point(0.5,0.5), Point(0.5,-0.5)]),
area_discretization=9.0,
rupture_mesh_spacing=1.0
)
site = Site(location=Point(0.0,0.0),
vs30=800.0,
vs30measured=True,
z1pt0=500.0,
z2pt5=2.0)
gsims = {'Active Shallow Crust': BooreAtkinson2008()}
imt = SA(period=0.1,damping=5.0)
iml = 0.2
time_span = 50.0
truncation_level = 3.0
n_epsilons = 3
mag_bin_width = 0.2
# in km
dist_bin_width = 10.0
# in decimal degree
coord_bin_width = 0.2
# compute disaggregation
bin_edges, diss_matrix = disagg.disaggregation_poissonian(
[src], site, imt, iml, gsims, time_span, truncation_level,
n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width
)
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins, trt_bins = bin_edges
numpy.testing.assert_almost_equal(
mag_bins, [5., 5.2, 5.4, 5.6, 5.8, 6., 6.2, 6.4, 6.6]
)
numpy.testing.assert_almost_equal(
dist_bins, [0., 10., 20., 30., 40., 50., 60., 70., 80.]
)
numpy.testing.assert_almost_equal(
lat_bins, [-0.6, -0.4, -0.2, 0., 0.2, 0.4, 0.6]
)
numpy.testing.assert_almost_equal(
lon_bins, [-0.6, -0.4, -0.2, 0., 0.2, 0.4, 0.6]
)
numpy.testing.assert_almost_equal(
eps_bins, [-3., -1., 1., 3.]
)
self.assertEqual(trt_bins, ['Active Shallow Crust'])
expected_matrix = numpy.fromstring("""\
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c5GFf9WB1V268MyfPF7x63F35rVpVbHw82hPnuKYYkB/ordPde07I1qO7ZsGoL6Mnt7RdpqM/UwF
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NpRJAfK4Qs8XqReSkY+u6eonXVBeRAqK/ohy3LXjZOi5/h2he0qoeUFB0Qv8H5mRW2E=\
""".decode('base64').decode('zip')).reshape((8, 8, 6, 6, 3, 1))
numpy.testing.assert_almost_equal(diss_matrix, expected_matrix)
def test_areasource(self):
nodalplane = NodalPlane(strike=0.0, dip=90.0, rake=0.0)
src = AreaSource(source_id='src_1',
name='area source',
tectonic_region_type='Active Shallow Crust',
mfd=TruncatedGRMFD(a_val=3.5,
b_val=1.0,
min_mag=5.0,
max_mag=6.5,
bin_width=0.1),
nodal_plane_distribution=PMF([(1.0, nodalplane)]),
hypocenter_distribution=PMF([(1.0, 5.0)]),
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=10.0,
magnitude_scaling_relationship=WC1994(),
rupture_aspect_ratio=1.0,
polygon=Polygon([
Point(-0.5, -0.5),
Point(-0.5, 0.5),
Point(0.5, 0.5),
Point(0.5, -0.5)
]),
area_discretization=9.0,
rupture_mesh_spacing=1.0)
site = Site(location=Point(0.0, 0.0),
vs30=800.0,
vs30measured=True,
z1pt0=500.0,
z2pt5=2.0)
gsims = {'Active Shallow Crust': BooreAtkinson2008()}
imt = SA(period=0.1, damping=5.0)
iml = 0.2
time_span = 50.0
truncation_level = 3.0
n_epsilons = 3
mag_bin_width = 0.2
# in km
dist_bin_width = 10.0
# in decimal degree
coord_bin_width = 0.2
# compute disaggregation
bin_edges, diss_matrix = disagg.disaggregation_poissonian(
[src], site, imt, iml, gsims, time_span, truncation_level,
n_epsilons, mag_bin_width, dist_bin_width, coord_bin_width)
mag_bins, dist_bins, lon_bins, lat_bins, eps_bins, trt_bins = bin_edges
numpy.testing.assert_almost_equal(
mag_bins, [5., 5.2, 5.4, 5.6, 5.8, 6., 6.2, 6.4, 6.6])
numpy.testing.assert_almost_equal(
dist_bins, [0., 10., 20., 30., 40., 50., 60., 70., 80.])
numpy.testing.assert_almost_equal(
lat_bins, [-0.6, -0.4, -0.2, 0., 0.2, 0.4, 0.6])
numpy.testing.assert_almost_equal(
lon_bins, [-0.6, -0.4, -0.2, 0., 0.2, 0.4, 0.6])
numpy.testing.assert_almost_equal(eps_bins, [-3., -1., 1., 3.])
self.assertEqual(trt_bins, ['Active Shallow Crust'])
expected_matrix = numpy.fromstring("""\
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lEYNKOeWBlNFyZDqd/q9vq+v8717da99zz5N9vs/S6+1nr3Ws/Y6e33W8ywIoiCVcM+brec1YbSo
fvtn5mYYmsTNHN+wGP7v/591TK2FLWEoO1H1caMJ/Dc1kcupjGMOYWy8PRQU/REWFiS31xqGLsZ2
ii9e+9WfsZAw3S0TeOUlR+7RFvWgn5clIg/vs6AGh2O0JfZf22VvFJ3UaQhDl1W0LgQtoeYdxd9j
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5tvrx/Q6tDslAO/DZeLQKwgwj56J7b4C8Ct0j/sSxS9CfK7egmYejFwi4bmwe/HrQ0ioJ3bwoFsY
CfUw20xFrgDq4Ry6axADKOcefm2X24fG13XcuGG3+5A93cHZvWT3eRLsnGfhUpUCqqfO0ecaCfUv
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tjrP6rnvdLVAhuKHn/D2UFD0R4Zr3R+WugSGRJ4u2juN/dWfZ/wSxkEMet7PnV5XltyYAUP175ct
zLP92u6KJQwDlgkMmdB2Xv/Rlpp3FH+PUo495AvQdxB4/nLvscLznya2vrPPbHz97rki6UXG+PLt
lon2BxYA9qslMcm3uoLbmW3XFtg5HV9PUHJeYwRAF6NZGjvdBOgL+ZnPO/+cILx+G5oXFpKFAMYr
eu9qfTVqvvcW2K+DG2yHAvzEwci6aRK+3Fo91FMToJOim8N/ow8RfBzZ0tCaVD0S/CHrED0aoPMS
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""".decode('base64').decode('zip')).reshape((8, 8, 6, 6, 3, 1))
numpy.testing.assert_almost_equal(diss_matrix, expected_matrix)
