def test_recurrence_collapse_branches(self):
'''
Tests the recurrence model generated by collapsing branches
'''
self.fault = mtkActiveFault('001',
'A Fault',
self.simple_fault, [(5., 0.5), (7., 0.5)],
0.,
None,
aseismic=0.,
msr_sigma=[(0.0, 1.0)],
neotectonic_fault=None,
scale_rel=[(WC1994(), 1.0)],
aspect_ratio=1.0,
shear_modulus=[(30., 1.0)],
disp_length_ratio=[(1.25E-5, 1.0)])
mfd_config = [{
'MFD_spacing': 0.1,
'Maximum_Magnitude': None,
'Minimum_Magnitude': 5.0,
'Model_Name': 'AndersonLucoArbitrary',
'Model_Weight': 0.7,
'Model_Type': 'First',
'b_value': [0.8, 0.05]
}, {
'MFD_spacing': 0.1,
'Maximum_Magnitude': None,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Name': 'YoungsCoppersmithExponential',
'Model_Weight': 0.3,
'b_value': [0.8, 0.05]
}]
# Enumerated branches should have four models
self.fault.generate_recurrence_models(collapse=True,
rendered_msr=WC1994(),
config=mfd_config)
expected_rates = 0.
expected_weights = np.array([0.35, 0.15, 0.35, 0.15])
for iloc in range(0, 4):
expected_rates = expected_rates + (expected_weights[iloc] *
10.**FAULT_RATE_DATA[iloc, :])
np.testing.assert_array_almost_equal(
np.log10(self.fault.mfd[0][0].occur_rates),
np.log10(expected_rates))
def __init__(self,
source_file,
id,
investigation_time,
start_date,
min_mag,
npd=NPD,
hdd=HDD,
aspect=1.5,
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=15.0,
msr=WC1994(),
mesh_spacing=1.0,
trt="Active Shallow Crust",
integration_distance=1000):
assert os.path.exists(source_file), source_file
self.source_file = source_file
self.source_id = id
self.inv_time = investigation_time
self.start_date = start_date
self.tom = self._get_tom()
self.min_mag = min_mag
self.npd = npd
self.hdd = hdd
self.aspect = aspect
self.usd = upper_seismogenic_depth
self.lsd = lower_seismogenic_depth
self.msr = msr
self.mesh_spacing = mesh_spacing
self.tectonic_region_type = trt
self.num_ruptures = 0 # not set yet
def __init__(self, magnitude, dip, aspect,
tectonic_region='Active Shallow Crust', rake=0., ztor=0.,
strike=0., msr=WC1994(), initial_point=DEFAULT_POINT,
hypocentre_location=None):
"""
Instantiate the rupture - requires a minimum of a magnitude, dip
and aspect ratio
"""
self.magnitude = magnitude
self.dip = dip
self.aspect = aspect
self.rake = rake
self.strike = strike
self.location = initial_point
self.ztor = ztor
self.trt = tectonic_region
self.hypo_loc = hypocentre_location
# If the top of rupture depth in the initial
if fabs(self.location.depth - self.ztor) > 1E-9:
self.location.depth = ztor
self.msr = msr
self.area = self.msr.get_median_area(self.magnitude, self.rake)
self.surface = create_planar_surface(self.location,
self.strike,
self.dip,
self.area,
self.aspect)
self.hypocentre = get_hypocentre_on_planar_surface(self.surface,
self.hypo_loc)
self.rupture = self.get_rupture()
self.target_sites_config = None
self.target_sites = None
def __init__(self,
source_file,
investigation_time,
start_date,
min_mag,
npd,
hdd,
aspect=1.5,
upper_seismogenic_depth=0.0,
lower_seismogenic_depth=15.0,
msr=WC1994(),
mesh_spacing=1.0,
trt="Active Shallow Crust",
integration_distance=1000):
assert os.path.exists(source_file), source_file
self.source_file = source_file
self.source_id = None # unset until .new is called
self.inv_time = investigation_time
self.start_date = start_date
self.temporal_occurrence_model = PoissonTOM(self.inv_time)
self.min_mag = min_mag
self.npd = npd
self.hdd = hdd
self.aspect = aspect
self.usd = upper_seismogenic_depth
self.lsd = lower_seismogenic_depth
self.msr = msr
self.mesh_spacing = mesh_spacing
self.tectonic_region_type = trt
self.stop = None
self.start = None
def setUp(self):
'''
'''
self.fault = None
self.regionalisation = None
self.msr = [(WC1994(), 1.0)]
self.msr_sigma = [(-1.5, 0.15), (0.0, 0.7), (1.5, 0.15)]
self.shear_mod = [(30.0, 0.8), (35.0, 0.2)]
self.dlr = [(1.25E-5, 1.0)]
self.config = [{}]
self.slip = [(10.0, 1.0)]
x0 = Point(30., 30., 0.)
x1 = x0.point_at(30., 0., 30.)
x2 = x1.point_at(30., 0., 60.)
# Total length is 60 km
self.trace = Line([x0, x1, x2])
self.dip = 90.
self.upper_depth = 0.
self.lower_depth = 20.
self.simple_fault = SimpleFaultGeometry(self.trace,
self.dip,
self.upper_depth,
self.lower_depth)
# Creates a trace ~60 km long made of 3 points
upper_edge = Line([x0, x1, x2])
lower_edge = Line([x0.point_at(40., 20., 130.),
x1.point_at(42., 25., 130.),
x2.point_at(41., 22., 130.)])
self.complex_fault = ComplexFaultGeometry([upper_edge, lower_edge],
2.0)
def test_generate_branching_index(self):
'''
Simple test to check that a correct branching index is raised
Slip - 2 values
MSR - 1 value
Shear Modulus - 2 value
DLR - 1 value
MSR_Sigma - 3 Values
Config - 1 value
'''
self.fault = mtkActiveFault('001',
'A Fault',
self.simple_fault, [(5., 0.5), (7., 0.5)],
0.,
None,
msr_sigma=[(-1.5, 0.15), (0., 0.7),
(1.5, 0.15)],
neotectonic_fault=None,
scale_rel=[(WC1994(), 1.0)],
aspect_ratio=1.0,
shear_modulus=[(28., 0.5), (30., 0.5)],
disp_length_ratio=[(1.25E-5, 1.0)])
# Set with only one config - no data input
self.fault.generate_config_set({})
expected_result = np.array(
[[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 2, 0],
[0, 0, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0], [0, 0, 1, 0, 2, 0],
[1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 1, 0], [1, 0, 0, 0, 2, 0],
[1, 0, 1, 0, 0, 0], [1, 0, 1, 0, 1, 0], [1, 0, 1, 0, 2, 0]],
dtype=int)
branch_index, number_branches = \
self.fault._generate_branching_index()
np.testing.assert_array_equal(branch_index, expected_result)
self.assertEqual(number_branches, 12)
def setUp(self):
mfd = TruncatedGRMFD(min_mag=4.0, max_mag=6.0, bin_width=0.1,
a_val=2.0, b_val=1.0)
msr = WC1994()
tom = PoissonTOM(1.0)
pol = Polygon([Point(longitude=0.0, latitude=0.0),
Point(longitude=1.0, latitude=0.0),
Point(longitude=1.0, latitude=1.0),
Point(longitude=0.0, latitude=1.0)])
npd = PMF([(1.0, NodalPlane(0.0, 90.0, 0.0))])
hpd = PMF([(0.7, 10.), (0.3, 20.0)])
self.src1 = AreaSource(source_id='1',
name='1',
tectonic_region_type='Test',
mfd=mfd,
rupture_mesh_spacing=1,
magnitude_scaling_relationship=msr,
rupture_aspect_ratio=1.,
temporal_occurrence_model=tom,
upper_seismogenic_depth=0,
lower_seismogenic_depth=100.,
nodal_plane_distribution=npd,
hypocenter_distribution=hpd,
polygon=pol,
area_discretization=10.)
def build_fault_model(self,
collapse=False,
rendered_msr=WC1994(),
mfd_config=None):
'''
Constructs a full fault model with epistemic uncertainty by
enumerating all the possible recurrence models of each fault as
separate faults, with the recurrence rates multiplied by the
corresponding weights.
:param bool collapse:
Determines whether or not to collapse the branches
:param rendered_msr:
If the option is taken to collapse the branches then a recurrence
model for rendering must be defined
:param list/dict mfd_config:
Universal list or dictionay of configuration parameters for the
magnitude frequency distribution - will overwrite whatever is
previously defined for the fault!
'''
self.source_model = mtkSourceModel(self.id, self.name)
for fault in self.faults:
fault.generate_recurrence_models(collapse,
config=mfd_config,
rendered_msr=rendered_msr)
src_model, src_weight = fault.generate_fault_source_model()
for iloc, model in enumerate(src_model):
new_model = deepcopy(model)
new_model.id = str(model.id) + '_%g' % (iloc + 1)
new_model.mfd.occurrence_rates = \
(np.array(new_model.mfd.occurrence_rates) *
src_weight[iloc]).tolist()
self.source_model.sources.append(new_model)
def prefilter_background_model(hdf5,
sites,
integration_distance,
msr=WC1994(),
aspect=1.5):
"""
Identify those points within the integration distance
:param sites:
Sites for consideration (can be None!)
:param float integration_distance:
Maximum distance from rupture to site for consideration
:param msr:
Magnitude scaling relation
:param float aspect:
Aspect ratio
:returns:
Boolean vector indicating if sites are within (True) or outside (False)
the integration distance
"""
bg_locations = hdf5["Grid/Locations"][:].astype("float64")
n_locations = bg_locations.shape[0]
if not sites:
# Apply no filtering - all sources valid
return numpy.ones(n_locations, dtype=bool)
distances = min_distance(sites.lons, sites.lats,
numpy.zeros_like(sites.lons), bg_locations[:, 0],
bg_locations[:, 1], numpy.zeros(n_locations))
# Add buffer equal to half of length of median area from Mmax
mmax_areas = msr.get_median_area(hdf5["Grid/MMax"][:], 0.0)
mmax_lengths = numpy.sqrt(mmax_areas / aspect)
return distances <= (0.5 * mmax_lengths + integration_distance)
def _parse_event_data(self, metadata):
"""
Read in the distance related metadata and return an instance of the
:class: smtk.sm_database.Earthquake
"""
metadata["MODY"] = metadata["MODY"].zfill(4)
metadata["HRMN"] = metadata["HRMN"].zfill(4)
# Date and Time
year = get_int(metadata["YEAR"])
month = get_int(metadata["MODY"][:2])
day = get_int(metadata["MODY"][2:])
hour = get_int(metadata["HRMN"][:2])
minute = get_int(metadata["HRMN"][2:])
eq_datetime = datetime(year, month, day, hour, minute)
# Event ID and Name
eq_id = metadata["EQID"]
eq_name = metadata["Earthquake Name"]
# Focal Mechanism
focal_mechanism = self._get_focal_mechanism(eq_id, eq_name, metadata)
focal_mechanism.scalar_moment = get_float(metadata["Mo (dyne.cm)"]) *\
1E-7
# Read magnitude
pref_mag = Magnitude(get_float(metadata["Earthquake Magnitude"]),
metadata["Magnitude Type"],
sigma=get_float(metadata["Uncertainty"]))
# Create Earthquake Class
eqk = Earthquake(eq_id, eq_name, eq_datetime,
get_float(metadata["Hypocenter Longitude (deg)"]),
get_float(metadata["Hypocenter Latitude (deg)"]),
get_float(metadata["Hypocenter Depth (km)"]),
pref_mag, focal_mechanism, metadata["Country"])
hypo_loc = (0.5, 0.7) # Hypocentre Location
msr = WC1994()
# Warning rake set to 0.0 in scaling relationship
area = msr.get_median_area(pref_mag.value, 0.0)
aspect_ratio = 1.5 # Assumed Fixed
width_model = np.sqrt(area / aspect_ratio)
length_model = aspect_ratio * width_model
ztor_model = eqk.depth - width_model / 2.
if ztor_model < 0:
ztor_model = 0.0
length = get_float(metadata["Fault Rupture Length (km)"])
if length is None:
length = length_model
width = get_float(metadata["Fault Rupture Width (km)"])
if width is None:
width = width_model
ztor = get_float(metadata["Depth to Top Of Fault Rupture Model"])
if ztor is None:
ztor = ztor_model
# Rupture
eqk.rupture = Rupture(eq_id, eq_name, pref_mag, length, width, ztor)
# get_float(metadata["Fault Rupture Length (km)"]),
# get_float(metadata["Fault Rupture Width (km)"]),
# get_float(metadata["Depth to Top Of Fault Rupture Model"]))
eqk.rupture.get_area()
return eqk
def sample_background_model(
hdf5, branch_key, tom, eff_num_ses, seed, filter_idx, min_mag, npd,
hdd, upper_seismogenic_depth, lower_seismogenic_depth, msr=WC1994(),
aspect=1.5, trt=DEFAULT_TRT):
"""
Generates a rupture set from a sample of the background model
:param branch_key:
Key to indicate the branch for selecting the background model
:param tom:
Temporal occurrence model as instance of :class:
openquake.hazardlib.tom.TOM
:param seed:
Random seed to use in the call to tom.sample_number_of_occurrences
:param filter_idx:
Sites for consideration (can be None!)
:param float min_mag:
Minimim magnitude for consideration of background sources
:param npd:
Nodal plane distribution as instance of :class:
openquake.hazardlib.pmf.PMF
:param hdd:
Hypocentral depth distribution as instance of :class:
openquake.hazardlib.pmf.PMF
:param float aspect:
Aspect ratio
:param float upper_seismogenic_depth:
Upper seismogenic depth (km)
:param float lower_seismogenic_depth:
Lower seismogenic depth (km)
:param msr:
Magnitude scaling relation
:param float integration_distance:
Maximum distance from rupture to site for consideration
"""
bg_magnitudes = hdf5["/".join(["Grid", branch_key, "Magnitude"])][()]
# Select magnitudes above the minimum magnitudes
mag_idx = bg_magnitudes >= min_mag
mags = bg_magnitudes[mag_idx]
rates = hdf5["/".join(["Grid", branch_key, "RateArray"])][filter_idx, :]
rates = rates[:, mag_idx]
valid_locs = hdf5["Grid/Locations"][filter_idx, :]
# Sample remaining rates
sampler = tom.sample_number_of_occurrences(rates * eff_num_ses, seed)
background_ruptures = []
background_n_occ = []
for i, mag in enumerate(mags):
rate_idx = numpy.where(sampler[:, i])[0]
rate_cnt = sampler[rate_idx, i]
occurrence = rates[rate_idx, i]
locations = valid_locs[rate_idx, :]
ruptures = generate_background_ruptures(
tom, locations, occurrence,
mag, npd, hdd, upper_seismogenic_depth,
lower_seismogenic_depth, msr, aspect, trt)
background_ruptures.extend(ruptures)
background_n_occ.extend(rate_cnt.tolist())
return background_ruptures, background_n_occ
def plot_planes_at(x,
y,
strikes,
dips,
magnitudes,
strike_cs,
dip_cs,
aratio=1.0,
msr=None,
ax=None,
zorder=20,
color='None',
linewidth=1,
axis=None):
"""
This plots a cross-section and number of rupture planes defined in terms
of a strike and a dip.
:parameter x:
Coordinates x on the cross-section
:parameter y:
Coordinates y on the cross-section (it corresponds to a depth)
:parameter strikes:
Strike values of the planes
:parameter dips:
Dip values of the planes
:parameter strike_cs:
Strike angle of the cross-section plane [in degrees]
:parameter dip_cs:
Dip angle of the cross-section plane [in degrees]
"""
if axis is None:
ax = plt.gca()
else:
plt.sca(axis)
if msr is None:
msr = WC1994()
cols = ['red', 'blue', 'green']
for strike, dip, col, mag in zip(strikes, dips, cols, magnitudes):
area = msr.get_median_area(mag, None)
width = (area / aratio)**.5
t = np.arange(-width / 2, width / 2, 0.1)
inter = get_line_of_intersection(strike, dip, strike_cs, dip_cs)
xl = t * inter[0]
yl = t * inter[1]
zl = t * inter[2]
ds = -np.sign(t) * (xl**2 + yl**2)**.5 + x
if color is not None:
col = color
plt.plot(ds, zl + y, zorder=zorder, color=col, linewidth=linewidth)
def generate_background_ruptures(tom,
locations,
occurrence,
mag,
npd,
hdd,
upper_seismogenic_depth,
lower_seismogenic_depth,
msr=WC1994(),
aspect=1.5,
trt=DEFAULT_TRT):
"""
:param tom:
Temporal occurrence model as instance of :class:
openquake.hazardlib.tom.TOM
:param numpy.ndarray locations:
Array of locations [Longitude, Latitude] of the point sources
:param numpy.ndarray occurrence:
Annual rates of occurrence
:param float mag:
Magnitude
:param npd:
Nodal plane distribution as instance of :class:
openquake.hazardlib.pmf.PMF
:param hdd:
Hypocentral depth distribution as instance of :class:
openquake.hazardlib.pmf.PMF
:param float upper_seismogenic_depth:
Upper seismogenic depth (km)
:param float lower_seismogenic_depth:
Lower seismogenic depth (km)
:param msr:
Magnitude scaling relation
:param float aspect:
Aspect ratio
:param str trt:
Tectonic region type
:returns:
List of ruptures
"""
ruptures = []
n_vals = len(locations)
depths = hdd.sample_pairs(n_vals)
nodal_planes = npd.sample_pairs(n_vals)
for i, (x, y) in enumerate(locations):
hypocentre = Point(x, y, depths[i][1])
surface = get_rupture_surface(mag, nodal_planes[i][1], hypocentre, msr,
aspect, upper_seismogenic_depth,
lower_seismogenic_depth)
rupture_probability = (occurrence[i] * nodal_planes[i][0] *
depths[i][0])
ruptures.append(
ParametricProbabilisticRupture(mag, nodal_planes[i][1].rake, trt,
hypocentre, surface, PointSource,
rupture_probability, tom))
return ruptures
def example_calc(apply):
sitecol = SiteCollection([
Site(Point(30.0, 30.0), 760., True, 1.0, 1.0),
Site(Point(30.25, 30.25), 760., True, 1.0, 1.0),
Site(Point(30.4, 30.4), 760., True, 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': akkar_bommer_2010.AkkarBommer2010()}
return calc_hazard_curves(sources, sitecol, imtls, gsims, apply=apply)
def test_parse_region_list_to_tuples(self):
'''
Tests the function to parse a region list to a set of tuples
'''
self.data = {
'Shear_Modulus': {
'Value': [30.],
'Weight': [1.0]
},
'Displacement_Length_Ratio': {
'Value': [1.25E-5],
'Weight': [1.0]
},
'Magnitude_Scaling_Relation': {
'Value': [WC1994()],
'Weight': [1.0]
}
}
expected_output = {
'Shear_Modulus': [(30., 1.0)],
'Displacement_Length_Ratio': [(1.25E-5, 1.0)],
'Magnitude_Scaling_Relation': [(WC1994(), 1.0)]
}
output = parse_tect_region_dict_to_tuples([self.data])
self.assertAlmostEqual(expected_output['Shear_Modulus'][0][0],
output[0]['Shear_Modulus'][0][0])
self.assertAlmostEqual(expected_output['Shear_Modulus'][0][1],
output[0]['Shear_Modulus'][0][1])
self.assertAlmostEqual(
expected_output['Displacement_Length_Ratio'][0][0],
output[0]['Displacement_Length_Ratio'][0][0])
self.assertAlmostEqual(
expected_output['Displacement_Length_Ratio'][0][1],
output[0]['Displacement_Length_Ratio'][0][1])
self.assertTrue(
isinstance(output[0]['Magnitude_Scaling_Relation'][0][0], WC1994))
self.assertAlmostEqual(
expected_output['Magnitude_Scaling_Relation'][0][1],
output[0]['Shear_Modulus'][0][1])
def nrml_from_shapefile(shapefile, shapefile_faultname_attribute,
shapefile_dip_attribute, shapefile_sliprate_attribute,
source_model_name, simple_fault_tectonic_region,
magnitude_scaling_relation, rupture_aspect_ratio,
upper_depth, lower_depth, a_value, b_value, min_mag,
max_mag, rake, output_dir, quiet):
"""Driver routine to convert nrml to shapefile
"""
# Get geometry
fault_traces, faultnames, dips, \
sliprate, fault_lengths = parse_line_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute)
# Output is written line-by-line to this list
output_xml = []
append_xml_header(output_xml, source_model_name)
# Loop through each fault and add source specific info
for i in range(len(fault_traces)):
simple_fault_id = i
A = fault_lengths[i] * (float(lower_depth) - float(upper_depth))
# Calculate M_max from scaling relations
scalrel = WC1994()
max_mag = scalrel.get_median_mag(A, float(rake))
# print A
# Calculate GR a values from slip rate
if sliprate[i] != '""':
print sliprate[i]
a_value, moment_rate = fault_slip_rate_GR_conversion.slip2GR(
sliprate[i], A, float(b_value), float(max_mag), M_min=0.0)
append_rupture_geometry(output_xml, fault_traces[i], dips[i],
simple_fault_id, faultnames[i], upper_depth,
lower_depth, simple_fault_tectonic_region)
append_earthquake_information(output_xml, magnitude_scaling_relation,
rupture_aspect_ratio, a_value, b_value,
min_mag, max_mag, rake)
# Close xml
output_xml.append(' </sourceModel>')
output_xml.append('</nrml>')
# Add newlines
output_xml = [oxml + '\n' for oxml in output_xml]
return output_xml
def test_collapse_fault_model(self):
input_file = os.path.join(
BASE_DATA_PATH, "collapse_test_simple_fault_example_4branch.yml")
mesh_spacing = 1.0
reader = FaultYmltoSource(input_file)
fault_model, tectonic_region = reader.read_file(mesh_spacing)
fault_model.build_fault_model(collapse=True,
bin_width=0.05,
rendered_msr=WC1994())
expected_mfd = self.src.incrementalMFD
model_mfd = fault_model.faults[0].mfd[0][0]
self.assertAlmostEqual(expected_mfd["binWidth"], model_mfd.bin_width,
7)
self.assertAlmostEqual(expected_mfd["minMag"], model_mfd.min_mag, 7)
expected_rates = np.array(expected_mfd.occurRates.text)
np.testing.assert_array_almost_equal(model_mfd.occur_rates,
expected_rates, 7)
def test_generate_recurrence_models_no_collapse(self):
'''
Tests the generate recurrence models option without collapsing
branches: simple example with two slip rates and two mfd configurations
'''
self.fault = mtkActiveFault(
'001',
'A Fault',
self.simple_fault,
[(5., 0.5), (7., 0.5)],
0.,
None,
aseismic=0.,
msr_sigma=[(0.0, 1.0)],
neotectonic_fault=None,
scale_rel=[(WC1994(), 1.0)],
aspect_ratio=1.0,
shear_modulus=[(30., 1.0)],
disp_length_ratio=[(1.25E-5, 1.0)])
mfd_config = [{'MFD_spacing': 0.1,
'Maximum_Magnitude': None,
'Minimum_Magnitude': 5.0,
'Model_Name': 'AndersonLucoArbitrary',
'Model_Weight': 0.7,
'Model_Type': 'First',
'b_value': [0.8, 0.05]},
{'MFD_spacing': 0.1,
'Maximum_Magnitude': None,
'Maximum_Magnitude_Uncertainty': None,
'Minimum_Magnitude': 5.0,
'Model_Name': 'YoungsCoppersmithExponential',
'Model_Weight': 0.3,
'b_value': [0.8, 0.05]}]
# Enumerates branches should have four models
self.fault.generate_recurrence_models(config=mfd_config)
mfds = self.fault.mfd[0]
weights = self.fault.mfd[1]
np.testing.assert_array_almost_equal(
weights,
np.array([0.35, 0.15, 0.35, 0.15]))
for (iloc, occur) in enumerate(mfds):
np.testing.assert_array_almost_equal(
np.log10(occur.occur_rates),
FAULT_RATE_DATA[iloc, :])
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 mag_scale_rel_to_hazardlib(mag_scale_rel, use_default=False):
"""
Returns the magnitude scaling relation in a format readable by
openquake.hazardlib
"""
if isinstance(mag_scale_rel, BaseMSR):
return mag_scale_rel
elif isinstance(mag_scale_rel, str):
if not mag_scale_rel in SCALE_RELS.keys():
raise ValueError('Magnitude scaling relation %s not supported!'
% mag_scale_rel)
else:
return SCALE_RELS[mag_scale_rel]()
else:
if use_default:
# Returns the Wells and Coppersmith string
return WC1994()
else:
raise ValueError('Magnitude Scaling Relation Not Defined!')
def setUp(self):
"""
"""
#
# coordinates of point sources
lons = [10.00, 10.10, 10.20, 10.00, 10.10, 10.20, 10.00, 10.10, 10.20]
lats = [45.10, 45.10, 45.10, 45.05, 45.05, 45.05, 45.00, 45.00, 45.00]
deps = [10.00, 10.00, 10.00, 10.00, 10.00, 10.00, 10.00, 10.00, 10.00]
self.lons = lons
self.lats = lats
#
# set main parameters
mfd = TruncatedGRMFD(min_mag=4.0,
max_mag=6.0,
bin_width=0.1,
a_val=2.0,
b_val=1.0)
msr = WC1994()
tom = PoissonTOM(1.0)
npd = PMF([(1.0, NodalPlane(0.0, 90.0, 0.0))])
hdd = PMF([(0.7, 4.), (0.3, 8.0)])
#
# create the list of sources
srcs = []
for idx, (lon, lat, dep) in enumerate(zip(lons, lats, deps)):
src = PointSource(source_id='1',
name='Test',
tectonic_region_type=TRT.ACTIVE_SHALLOW_CRUST,
mfd=mfd,
rupture_mesh_spacing=5.0,
magnitude_scaling_relationship=msr,
rupture_aspect_ratio=1.0,
temporal_occurrence_model=tom,
upper_seismogenic_depth=0,
lower_seismogenic_depth=10.,
location=Point(lon, lat, dep),
nodal_plane_distribution=npd,
hypocenter_distribution=hdd)
srcs.append(src)
self.points = srcs
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 nrml_from_shapefile(shapefile, shapefile_faultname_attribute,
shapefile_dip_attribute, shapefile_sliprate_attribute,
source_model_name, simple_fault_tectonic_region,
magnitude_scaling_relation, rupture_aspect_ratio,
upper_depth, lower_depth, a_value, b_value, min_mag,
max_mag, rake, output_dir, incremental_mfd, quiet):
"""Driver routine to convert nrml to shapefile
"""
# Get geometry
fault_traces, faultnames, dips, \
sliprate, fault_lengths = parse_line_shapefile(shapefile,
shapefile_faultname_attribute,
shapefile_dip_attribute,
shapefile_sliprate_attribute)
# Output is written line-by-line to this list
output_xml = []
append_xml_header(output_xml, source_model_name)
# Loop through each fault and add source specific info
for i in range(len(fault_traces)):
simple_fault_id = i
A = fault_lengths[i] * (float(lower_depth) - float(upper_depth))
# Calculate M_max from scaling relations
scalrel = WC1994()
bin_width = 0.1
max_mag = scalrel.get_median_mag(A, float(rake))
char_mag = max_mag - 0.25 #characteristic magnitude for OQ def
# print A
# Calculate characteristic incremental occurrence rates from slip rate
if sliprate[i] != '""':
print sliprate[i]
# just to calculate the moment rate, need to fix this function
a_value, moment_rate = fault_slip_rate_GR_conversion.slip2GR(
sliprate[i], A, float(b_value), float(max_mag), M_min=0.0)
a_value = None # We aren't using the a value
# mfd = YoungsCoppersmith1985MFD.from_total_moment_rate(min_mag=min_mag,
# b_val=float(b_value),
# char_mag=float(max_mag),
# total_moment_rate=moment_rate,
# bin_width=0.1)
# mags,rates=zip(*mfd.get_annual_occurrence_rates())
append_rupture_geometry(output_xml, fault_traces[i], dips[i],
simple_fault_id, faultnames[i], upper_depth,
lower_depth, simple_fault_tectonic_region)
if incremental_mfd:
append_earthquake_information_inc(output_xml,
magnitude_scaling_relation,
rupture_aspect_ratio, char_mag,
b_value, min_mag, max_mag, rake,
moment_rate, bin_width)
else:
append_earthquake_information_YC(output_xml,
magnitude_scaling_relation,
rupture_aspect_ratio, char_mag,
b_value, min_mag, max_mag, rake,
moment_rate, bin_width)
# Close xml
output_xml.append(' </sourceModel>')
output_xml.append('</nrml>')
# Add newlines
output_xml = [oxml + '\n' for oxml in output_xml]
return output_xml
# Get a list of the available GSIMs
AVAILABLE_GSIMS = gsim.get_available_gsims()
# Generic dictionary of parameters needed for a trellis calculation
PARAM_DICT = {
'magnitudes': [],
'distances': [],
'distance_type': 'rjb',
'vs30': [],
'strike': None,
'dip': None,
'rake': None,
'ztor': None,
'hypocentre_location': (0.5, 0.5),
'hypo_loc': (0.5, 0.5),
'msr': WC1994()
}
# Defines the plotting units for given intensitiy measure type
PLOT_UNITS = {
'PGA': 'g',
'PGV': 'cm/s',
'SA': 'g',
'IA': 'm/s',
'CSV': 'g-sec',
'RSD': 's',
'MMI': ''
}
# Verbose label for each given distance type
DISTANCE_LABEL_MAP = {
def setUp(self):
self.asr = WC1994()
def _parse_distance_data(self, event, site, metadata):
"""
Read in the distance related metadata and return an instance of the
:class: smtk.sm_database.RecordDistance
"""
# Compute various distance metrics
# Add calculation of Repi, Rhypo from event and station localizations
# (latitudes, longitudes, depth, elevation)?
target_site = Mesh(np.array([site.longitude]),
np.array([site.latitude]),
np.array([-site.altitude / 1000.0]))
# Warning ratio fixed to 1.5
ratio = 1.5
if not event.rupture.area:
event.rupture.area = WC1994().get_median_area(
event.magnitude.value, None)
surface_modeled = rcfg.create_planar_surface(
Point(event.longitude, event.latitude, event.depth),
event.mechanism.nodal_planes.nodal_plane_1['strike'],
event.mechanism.nodal_planes.nodal_plane_1['dip'],
event.rupture.area, ratio)
hypocenter = rcfg.get_hypocentre_on_planar_surface(
surface_modeled, event.rupture.hypo_loc)
try:
surface_modeled._create_mesh()
except:
dip = surface_modeled.get_dip()
dip_dir = (surface_modeled.get_strike() - 90.) % 360.
ztor = surface_modeled.top_left.depth
d_x = ztor * np.tan(np.radians(90.0 - dip))
top_left_surface = surface_modeled.top_left.point_at(
d_x, -ztor, dip_dir)
top_left_surface.depth = 0.
top_right_surface = surface_modeled.top_right.point_at(
d_x, -ztor, dip_dir)
top_right_surface.depth = 0.
surface_modeled = SimpleFaultSurface.from_fault_data(
Line([top_left_surface,
top_right_surface]), surface_modeled.top_left.depth,
surface_modeled.bottom_left.depth, surface_modeled.get_dip(),
1.0)
# Rhypo
Rhypo, Repi, Rrup, Rjb, Ry0 = tuple(
map(get_positive_float, [
metadata[key] for key in [
"Hypocentral Distance (km)", "Epicentral Distance (km)",
"Rupture Distance (km)", "Joyner-Boore Distance (km)",
"Ry0 (km)"
]
]))
Rx = get_float(metadata["Rx (km)"]) # Rx can be negative
#Rhypo = get_float(metadata["Hypocentral Distance (km)"])
if Rhypo is None or Rhypo < 0.0:
Rhypo = hypocenter.distance_to_mesh(target_site)
# Repi
#Repi = get_float(metadata["Epicentral Distance (km)"])
if Repi is None or Repi < 0.0:
Repi = hypocenter.distance_to_mesh(target_site, with_depths=False)
# Rrup
#Rrup = get_float(metadata["Rupture Distance (km)"])
if Rrup is None or Rrup < 0.0:
Rrup = surface_modeled.get_min_distance(target_site)[0]
# Rjb
#Rjb = get_float(metadata["Joyner-Boore Distance (km)"])
if Rjb is None or Rjb < 0.0:
Rjb = surface_modeled.get_joyner_boore_distance(target_site)[0]
# Need to check if Rx and Ry0 are consistant with the other metrics
# when those are coming from the flatfile?
# Rx
#Rx = get_float(metadata["Rx (km)"])
if Rx is None or Rx < 0.0:
Rx = surface_modeled.get_rx_distance(target_site)[0]
# Ry0
Ry0 = get_float(metadata["Ry0 (km)"])
if Ry0 is None or Ry0 < 0.0:
Ry0 = surface_modeled.get_ry0_distance(target_site)[0]
distance = RecordDistance(repi=Repi,
rhypo=Rhypo,
rjb=Rjb,
rrup=Rrup,
r_x=Rx,
ry0=Ry0)
distance.azimuth = get_float(metadata["Source to Site Azimuth (deg)"])
#distance.hanging_wall = get_float(metadata["FW/HW Indicator"])
if metadata["FW/HW Indicator"] == "HW":
distance.hanging_wall = True
elif metadata["FW/HW Indicator"] == "FW":
distance.hanging_wall = False
else:
pass
return distance
return
# The GEM Foundation, and the authors of the software, assume no
# liability for use of the software.
'''
:mod: hmtk.regionalisation.tectonic_regionalisation implements the
hmtk.ancillary.tectonic_regionalisation.TectonicRegion :class:, defining
the methods and attributes associated with a region, and the
hmtk.ancillary.tectonic_regionalisation.TectonicRegionalisation :class:
defining a regionalisation as a set of regions
'''
from math import fabs
import numpy as np
from openquake.hazardlib.scalerel.wc1994 import WC1994
DEFAULT_SHEAR_MODULUS = [(30.0, 1.0)]
DEFAULT_DLR = [(1.25E-5, 1.0)]
DEFAULT_MSR = [(WC1994(), 1.0)]
def _check_list_weights(parameter, name):
'''
Checks that the weights in a list of tuples sums to 1.0
'''
if not isinstance(parameter, list):
raise ValueError('%s must be formulated with a list of tuples' % name)
weight = np.sum([val[1] for val in parameter])
if fabs(weight - 1.) > 1E-8:
raise ValueError('%s weights do not sum to 1.0!' % name)
return parameter
#~ if isinstance(parameter, dict):
#~ if isinstance(parameter['Model'], float):
def setUp(self):
"""
"""
self.msr = WC1994()
def test_build_fault_model(self):
# Tests the constuction of a fault model with two faults (1 simple,
# 1 complex) each with two mfd rates - should produce four sources
self.model = mtkActiveFaultModel('001', 'A Fault Model', faults=[])
x0 = Point(30., 30., 0.)
x1 = x0.point_at(30., 0., 30.)
x2 = x1.point_at(30., 0., 60.)
# Total length is 60 km
trace = Line([x0, x1, x2])
simple_fault = SimpleFaultGeometry(trace, 90., 0., 20.)
# Creates a trace ~60 km long made of 3 points
upper_edge = Line([x0, x1, x2])
lower_edge = Line([
x0.point_at(40., 20., 130.),
x1.point_at(42., 25., 130.),
x2.point_at(41., 22., 130.)
])
complex_fault = ComplexFaultGeometry([upper_edge, lower_edge], 2.0)
config = [{
'MFD_spacing': 0.1,
'Maximum_Magnitude': 7.0,
'Maximum_Uncertainty': None,
'Model_Name': 'Characteristic',
'Model_Weight': 0.5,
'Sigma': 0.1,
'Lower_Bound': -1.,
'Upper_Bound': 1.
}, {
'MFD_spacing': 0.1,
'Maximum_Magnitude': 7.5,
'Maximum_Uncertainty': None,
'Model_Name': 'Characteristic',
'Model_Weight': 0.5,
'Sigma': 0.1,
'Lower_Bound': -1.,
'Upper_Bound': 1.
}]
fault1 = mtkActiveFault('001',
'Simple Fault 1',
simple_fault, [(10.0, 1.0)],
-90.,
None,
aspect_ratio=1.0,
scale_rel=[(WC1994(), 1.0)],
shear_modulus=[(30.0, 1.0)],
disp_length_ratio=[(1E-5, 1.0)])
fault1.generate_config_set(config)
fault2 = mtkActiveFault('002',
'Complex Fault 1',
complex_fault, [(10.0, 1.0)],
-90.,
None,
aspect_ratio=1.0,
scale_rel=[(WC1994(), 1.0)],
shear_modulus=[(30.0, 1.0)],
disp_length_ratio=[(1E-5, 1.0)])
fault2.generate_config_set(config)
self.model.faults = [fault1, fault2]
# Generate source model
self.model.build_fault_model()
self.assertEqual(len(self.model.source_model.sources), 4)
# First source should be an instance of a mtkSimpleFaultSource
model1 = self.model.source_model.sources[0]
self.assertTrue(isinstance(model1, mtkSimpleFaultSource))
self.assertEqual(model1.id, '001_1')
self.assertAlmostEqual(model1.mfd.min_mag, 6.9)
np.testing.assert_array_almost_equal(
np.log10(np.array(model1.mfd.occurrence_rates)),
np.array([-2.95320041, -2.54583708, -2.953200413]))
# Second source should be an instance of a mtkSimpleFaultSource
model2 = self.model.source_model.sources[1]
self.assertTrue(isinstance(model2, mtkSimpleFaultSource))
self.assertEqual(model2.id, '001_2')
self.assertAlmostEqual(model2.mfd.min_mag, 7.4)
np.testing.assert_array_almost_equal(
np.log10(np.array(model2.mfd.occurrence_rates)),
np.array([-3.70320041, -3.29583708, -3.70320041]))
# Third source should be an instance of a mtkComplexFaultSource
model3 = self.model.source_model.sources[2]
self.assertTrue(isinstance(model3, mtkComplexFaultSource))
self.assertEqual(model3.id, '002_1')
self.assertAlmostEqual(model3.mfd.min_mag, 6.9)
np.testing.assert_array_almost_equal(
np.log10(np.array(model3.mfd.occurrence_rates)),
np.array([-2.59033387, -2.18297054, -2.59033387]))
# Fourth source should be an instance of a mtkComplexFaultSource
model4 = self.model.source_model.sources[3]
self.assertTrue(isinstance(model4, mtkComplexFaultSource))
self.assertEqual(model4.id, '002_2')
self.assertAlmostEqual(model4.mfd.min_mag, 7.4)
np.testing.assert_array_almost_equal(
np.log10(np.array(model4.mfd.occurrence_rates)),
np.array([-3.34033387, -2.93297054, -3.34033387]))
def _parse_event_data(self, metadata):
"""
Read in the distance related metadata and return an instance of the
:class: smtk.sm_database.Earthquake
"""
data_fields = ['Month', 'Day', 'Hour', 'Minute', 'Second']
for f in data_fields:
metadata[f] = metadata[f].zfill(2)
# Date and Time
year = get_int(metadata["Year"])
month = get_int(metadata["Month"])
day = get_int(metadata["Day"])
hour = get_int(metadata["Hour"])
minute = get_int(metadata["Minute"])
second = get_int(metadata["Second"])
eq_datetime = datetime(year, month, day, hour, minute, second)
# Event ID and Name
eq_id = metadata["EQID"]
eq_name = metadata["Earthquake Name"]
# Focal Mechanism
focal_mechanism = self._get_focal_mechanism(eq_id, eq_name, metadata)
focal_mechanism.scalar_moment = get_float(metadata["Mo (dyne.cm)"]) *\
1E-7
# Read magnitude
pref_mag = Magnitude(get_float(metadata["Magnitude"]),
metadata["Magnitude type"],
sigma=get_float(metadata["Magnitude uncertainty"]))
# Create Earthquake Class
eqk = Earthquake(eq_id, eq_name, eq_datetime,
get_float(metadata["Epicenter Longitude (deg; positive E)"]),
get_float(metadata["Epicenter Latitude (deg; positive N)"]),
get_float(metadata["Hypocenter Depth (km)"]),
pref_mag,
focal_mechanism,
metadata["Country"])
# hypocenter location
f1 = get_float(metadata[
"Along-strike Hypocenter location " +
"on the fault (fraction between 0 and 1)"])
f2 = get_float(metadata[
"Along-width Hypocenter location " +
"on the fault (fraction between 0 and 1)"])
if f1 is None or f2 is None:
hypo_loc = (0.5, 0.7)
else:
hypo_loc = (f1, f2)
evt_tectonic_region = metadata["Tectonic environment (Crustal; Inslab; Interface; Stable; Geothermal; Volcanic; Oceanic_crust)"]
if evt_tectonic_region == "Stable" or evt_tectonic_region == "Crustal":
msr=WC1994()
elif evt_tectonic_region == "Inslab":
msr=StrasserIntraslab()
elif evt_tectonic_region == "Interface":
msr=StrasserInterface()
# Warning rake set to 0.0 in scaling relationship - applies only
# to WC1994
area = msr.get_median_area(pref_mag.value, 0.0)
aspect_ratio = 1.5
width_model = np.sqrt(area / aspect_ratio)
length_model = aspect_ratio * width_model
ztor_model = eqk.depth - width_model / 2.
if ztor_model < 0:
ztor_model = 0.0
length = get_float(metadata["Fault Rupture Length (km)"])
if length is None:
length = length_model
width = get_float(metadata["Fault Rupture Width (km)"])
if width is None:
width = width_model
ztor = get_float(metadata["Depth to Top Of Fault Rupture Model"])
if ztor is None:
ztor=ztor_model
# Rupture
eqk.rupture = Rupture(eq_id,
length,
width,
ztor,
hypo_loc=hypo_loc)
# get_float(metadata["Fault Rupture Length (km)"]),
# get_float(metadata["Fault Rupture Width (km)"]),
# get_float(metadata["Depth to Top Of Fault Rupture Model"]),
# hypo_loc=hypo_loc)
eqk.rupture.get_area()
return eqk
