def test_fromTrace():
xp0 = [0.0]
xp1 = [0.0]
yp0 = [0.0]
yp1 = [0.05]
zp = [0.0]
widths = [10.0]
dips = [45.0]
# Rupture requires an origin even when not used:
origin = Origin({'eventsourcecode': 'test', 'lat': 0, 'lon': 0,
'depth': 5.0, 'mag': 7.0})
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths,
dips, origin,
reference='From J Smith, (personal communication)')
fstr = io.StringIO()
rupture.writeTextFile(fstr)
xp0 = [-121.81529, -121.82298]
xp1 = [-121.82298, -121.83068]
yp0 = [37.73707, 37.74233]
yp1 = [37.74233, 37.74758]
zp = [10, 15]
widths = [15.0, 20.0]
dips = [30.0, 45.0]
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths,
dips, origin,
reference='From J Smith, (personal communication)')
def test_map_rupture(interactive=False):
xp0 = np.array([-90.898000])
xp1 = np.array([-91.308000])
yp0 = np.array([12.584000])
yp1 = np.array([12.832000])
zp = [0.0]
strike = azimuth(yp0[0], xp0[0], yp1[0], xp1[0])
origin = Origin({
'lat': 0.0,
'lon': 0.0,
'depth': 0.0,
'mag': 5.5,
'eventsourcecode': 'abcd'
})
interface_width = MAX_DEPTH / np.sin(np.radians(DIP))
widths = np.ones(xp0.shape) * interface_width
dips = np.ones(xp0.shape) * DIP
strike = [strike]
rupture = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
origin,
strike=strike)
map_rupture(rupture)
if interactive:
fname = os.path.join(os.path.expanduser('~'), 'rupture_map.png')
plt.savefig(fname)
print('Rupture map plot saved to %s. Delete this file if you wish.' %
fname)
def test_slip():
# Rupture requires an origin even when not used:
origin = Origin({
'id': 'test',
'lon': 0,
'lat': 0,
'depth': 5.0,
'mag': 7.0,
'netid': 'us',
'network': '',
'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
# Make a rupture
lat0 = np.array([34.1])
lon0 = np.array([-118.2])
lat1 = np.array([34.2])
lon1 = np.array([-118.15])
z = np.array([1.0])
W = np.array([3.0])
dip = np.array([30.])
rup = QuadRupture.fromTrace(lon0, lat0, lon1, lat1, z, W, dip, origin)
slp = get_quad_slip(rup.getQuadrilaterals()[0], 30).getArray()
slpd = np.array([0.80816457, 0.25350787, 0.53160491])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector(22, 30, 86).getArray()
slpd = np.array([0.82714003, 0.38830563, 0.49878203])
np.testing.assert_allclose(slp, slpd)
def rupture_from_dict(d):
"""
Method returns either a Rupture subclass (QuadRupture, EdgeRupture, or
PointRupture) object based on a GeoJSON dictionary.
.. seealso::
:func:`rupture_from_dict_and_origin`
Args:
d (dict): Rupture GeoJSON dictionary, which must contain origin
information in the 'metadata' field.
Returns:
a Rupture subclass.
"""
validate_json(d)
origin = Origin(d['metadata'])
# What type of rupture is this?
geo_type = d['features'][0]['geometry']['type']
if geo_type == 'MultiPolygon':
# EdgeRupture will have 'mesh_dx' in metadata
if 'mesh_dx' in d['metadata']:
mesh_dx = d['metadata']['mesh_dx']
rupt = EdgeRupture(d, origin, mesh_dx=mesh_dx)
else:
rupt = QuadRupture(d, origin)
elif geo_type == 'Point':
rupt = PointRupture(origin)
return rupt
def test_slip():
# Rupture requires an origin even when not used:
origin = Origin({
'id': 'test',
'lon': 0,
'lat': 0,
'depth': 5.0,
'mag': 7.0,
'netid': 'us',
'network': '',
'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
# Make a rupture
lat0 = np.array([34.1])
lon0 = np.array([-118.2])
lat1 = np.array([34.2])
lon1 = np.array([-118.15])
z = np.array([1.0])
W = np.array([3.0])
dip = np.array([30.])
rup = QuadRupture.fromTrace(lon0, lat0, lon1, lat1, z, W, dip, origin)
slp = get_quad_slip(rup.getQuadrilaterals()[0], 30).getArray()
slpd = np.array([0.80816457, 0.25350787, 0.53160491])
np.testing.assert_allclose(slp, slpd)
slp = get_quad_strike_vector(rup.getQuadrilaterals()[0]).getArray()
slpd = np.array([0.58311969, 0.27569625, 0.76417472])
np.testing.assert_allclose(slp, slpd)
slp = get_quad_down_dip_vector(rup.getQuadrilaterals()[0]).getArray()
slpd = np.array([0.81219873, -0.17763484, -0.55567895])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector(22, 30, 86).getArray()
slpd = np.array([0.82714003, 0.38830563, 0.49878203])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector_DS(22, 30, -86).getArray()
slpd = np.array([-0.80100879, -0.32362856, -0.49878203])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector_SS(22, 80, 5).getArray()
slpd = np.array([0.3731811, 0.92365564, 0.])
np.testing.assert_allclose(slp, slpd)
mech = rake_to_mech(-160)
assert mech == 'SS'
mech = rake_to_mech(0)
assert mech == 'SS'
mech = rake_to_mech(160)
assert mech == 'SS'
mech = rake_to_mech(-80)
assert mech == 'NM'
mech = rake_to_mech(80)
assert mech == 'RS'
def test_ss3_m4p5():
magnitude = 4.5
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = OrthographicProjection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin
origin = Origin({'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'id': 'ss3',
'netid': '',
'network': '',
'locstring': '',
'rake': rake,
'time': HistoricTime.utcfromtimestamp(int(time.time()))})
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.]])
np.testing.assert_allclose(
fd, fd_test, rtol=1e-4)
def test_EdgeRupture_vs_QuadRupture():
# Sites stuff
sites = Sites.fromCenter(-122.15, 37.15, 1.5, 1.5, 0.01, 0.01)
sm_dict = sites._GeoDict
west = sm_dict.xmin
east = sm_dict.xmax
south = sm_dict.ymin
north = sm_dict.ymax
nx = sm_dict.nx
ny = sm_dict.ny
lats = np.linspace(north, south, ny)
lons = np.linspace(west, east, nx)
lon, lat = np.meshgrid(lons, lats)
dep = np.zeros_like(lon)
# Construct QuadRupture
xp0 = np.array([-122.0, -122.5])
yp0 = np.array([37.1, 37.4])
xp1 = np.array([-121.7, -122.3])
yp1 = np.array([37.2, 37.2])
zp = np.array([0, 6])
widths = np.array([30, 20])
dips = np.array([30, 40])
origin = Origin({
'lat': 33.15,
'lon': -122.15,
'depth': 0,
'mag': 7.2,
'id': '',
'netid': '',
'network': '',
'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
qrup = QuadRupture.fromTrace(xp0, yp0, xp1, yp1, zp, widths, dips, origin)
rrup_q = qrup.computeRrup(lon, lat, dep)
rjb_q = qrup.computeRjb(lon, lat, dep)
# Construct equivalent EdgeRupture
toplons = np.array([-122.0, -121.7, -122.5, -122.3])
toplats = np.array([37.1, 37.2, 37.4, 37.2])
topdeps = np.array([0, 0, 6, 6])
botlons = np.array([-121.886864, -121.587568, -122.635467, -122.435338])
botlats = np.array([36.884527, 36.984246, 37.314035, 37.114261])
botdeps = np.array([15.0000, 14.9998, 18.8558, 18.8559])
group_index = [0, 0, 1, 1]
erup = EdgeRupture.fromArrays(toplons, toplats, topdeps, botlons, botlats,
botdeps, origin, group_index)
rrup_e = erup.computeRrup(lon, lat, dep)
rjb_e = erup.computeRjb(lon, lat, dep)
# Check that QuadRupture and EdgeRupture give the same result
# (we check the absolute values of QuadRupture elsewhere)
np.testing.assert_allclose(rrup_e, rrup_q, atol=0.35)
np.testing.assert_allclose(rjb_e, rjb_q, atol=0.35)
def test_ss3_m4p5():
magnitude = 4.5
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin
origin = Origin({'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake})
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.]])
np.testing.assert_allclose(
fd, fd_test, rtol=1e-4)
def test_EdgeRupture_vs_QuadRupture():
# Sites stuff
sites = Sites.fromCenter(-122.15, 37.15, 1.5, 1.5, 0.01, 0.01)
sm_dict = sites._GeoDict
west = sm_dict.xmin
east = sm_dict.xmax
south = sm_dict.ymin
north = sm_dict.ymax
nx = sm_dict.nx
ny = sm_dict.ny
lats = np.linspace(north, south, ny)
lons = np.linspace(west, east, nx)
lon, lat = np.meshgrid(lons, lats)
dep = np.zeros_like(lon)
# Construct QuadRupture
xp0 = np.array([-122.0, -122.5])
yp0 = np.array([37.1, 37.4])
xp1 = np.array([-121.7, -122.3])
yp1 = np.array([37.2, 37.2])
zp = np.array([0, 6])
widths = np.array([30, 20])
dips = np.array([30, 40])
origin = Origin({'lat': 0, 'lon': 0, 'depth': 0, 'mag': 7.2, 'eventsourcecode': ''})
qrup = QuadRupture.fromTrace(xp0, yp0, xp1, yp1, zp, widths, dips, origin)
rrup_q = qrup.computeRrup(lon, lat, dep)
rjb_q = qrup.computeRjb(lon, lat, dep)
# Construct equivalent EdgeRupture
toplons = np.array([-122.0, -121.7, -122.5, -122.3])
toplats = np.array([37.1, 37.2, 37.4, 37.2])
topdeps = np.array([0, 0, 6, 6])
botlons = np.array([-121.886864, -121.587568, -122.635467, -122.435338])
botlats = np.array([36.884527, 36.984246, 37.314035, 37.114261])
botdeps = np.array([15.0000, 14.9998, 18.8558, 18.8559])
group_index = [0, 0, 1, 1]
erup = EdgeRupture.fromArrays(
toplons, toplats, topdeps, botlons, botlats, botdeps,
origin, group_index)
rrup_e = erup.computeRrup(lon, lat, dep)
rjb_e = erup.computeRjb(lon, lat, dep)
# Check that QuadRupture and EdgeRupture give the same result
# (we check the absolute values of QuadRupture elsewhere)
np.testing.assert_allclose(rrup_e, rrup_q, atol=0.35)
np.testing.assert_allclose(rjb_e, rjb_q, atol=0.35)
def test_plot_rupture(interactive=False):
xp0 = np.array([-90.898000])
xp1 = np.array([-91.308000])
yp0 = np.array([12.584000])
yp1 = np.array([12.832000])
zp = [0.0]
strike = azimuth(yp0[0], xp0[0], yp1[0], xp1[0])
origin = Origin({
'lat': 0.0,
'lon': 0.0,
'depth': 0.0,
'mag': 5.5,
'id': '',
'netid': 'abcd',
'network': '',
'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
interface_width = MAX_DEPTH / np.sin(np.radians(DIP))
widths = np.ones(xp0.shape) * interface_width
dips = np.ones(xp0.shape) * DIP
strike = [strike]
rupture = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
origin,
strike=strike)
plot_rupture_wire3d(rupture)
if interactive:
fname = os.path.join(os.path.expanduser('~'), 'rupture_wire_plot.png')
plt.savefig(fname)
print('Wire 3D plot saved to %s. Delete this file if you wish.' %
fname)
# Need to get tests to check exception for if an axis is handed off
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plot_rupture_wire3d(rupture, ax)
# And raise the exception if it is not a 3d axis
with pytest.raises(TypeError):
ax = fig.add_subplot(111)
plot_rupture_wire3d(rupture, ax)
def rupture_from_dict(d):
"""
Method returns either a Rupture subclass (QuadRupture, EdgeRupture, or
PointRupture) object based on a GeoJSON dictionary.
.. seealso::
:func:`rupture_from_dict_and_origin`
Args:
d (dict):
Rupture GeoJSON dictionary, which must contain origin
information in the 'metadata' field.
Returns:
a Rupture subclass.
"""
validate_json(d)
# We don't want to mess with the input just in case it gets used again
d = copy.deepcopy(d)
try:
d['metadata']['time'] = HistoricTime.strptime(d['metadata']['time'],
constants.TIMEFMT)
except ValueError:
d['metadata']['time'] = HistoricTime.strptime(d['metadata']['time'],
constants.ALT_TIMEFMT)
origin = Origin(d['metadata'])
# What type of rupture is this?
geo_type = d['features'][0]['geometry']['type']
if geo_type == 'MultiPolygon':
valid_quads = is_quadrupture_class(d)
if valid_quads is True:
rupt = QuadRupture(d, origin)
elif 'mesh_dx' in d['metadata']:
# EdgeRupture will have 'mesh_dx' in metadata
mesh_dx = d['metadata']['mesh_dx']
rupt = EdgeRupture(d, origin, mesh_dx=mesh_dx)
else:
raise ValueError('Invalid rupture dictionary.')
elif geo_type == 'Point':
rupt = PointRupture(origin)
return rupt
def rupture_from_dict_and_origin(rupdict, origin, mesh_dx=0.5):
"""
Method returns either a QuadRupture or EdgeRupture object based on a
GeoJSON dictionary and an origin. Note that this is very similar to
:func:`rupture_from_dict`, except that method is for
constructing the rupture objects from a dict that already contains the
origin info in the `metadata` field (e.g., from a dict from a Shakemap
container), while this method is for construction of the rupture objects
from a GeoJSON dict that does not yet include that information (e.g., from
a dict that is read in to initially create the shakemap container, along
with an Origin that is derived from `event.xml`).
.. seealso:: :func:`rupture_from_dict`
Args:
rupdictd (dict):
Rupture GeoJSON dictionary.
origin (Origin):
A ShakeMap origin object.
mesh_dx (float):
Target spacing (in km) for rupture discretization;
default is 0.5 km and it is only used if the rupture file is an
EdgeRupture.
Returns:
a Rupture subclass.
"""
validate_json(rupdict)
# Is this a QuadRupture or an EdgeRupture?
valid_quads = is_quadrupture_class(rupdict)
if valid_quads is True:
rupt = QuadRupture(rupdict, origin)
else:
if rupdict['features'][0]['geometry']['type'] == 'Point':
rupt = PointRupture(origin)
else:
rupt = EdgeRupture(rupdict, origin, mesh_dx=mesh_dx)
return rupt
def test_slip():
# Rupture requires an origin even when not used:
origin = Origin({'eventsourcecode': 'test', 'lat': 0, 'lon': 0,
'depth': 5.0, 'mag': 7.0})
# Make a rupture
lat0 = np.array([34.1])
lon0 = np.array([-118.2])
lat1 = np.array([34.2])
lon1 = np.array([-118.15])
z = np.array([1.0])
W = np.array([3.0])
dip = np.array([30.])
rup = QuadRupture.fromTrace(lon0, lat0, lon1, lat1, z, W, dip, origin)
slp = get_quad_slip(rup.getQuadrilaterals()[0], 30).getArray()
slpd = np.array([0.80816457, 0.25350787, 0.53160491])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector(22, 30, 86).getArray()
slpd = np.array([0.82714003, 0.38830563, 0.49878203])
np.testing.assert_allclose(slp, slpd)
def test_plot_rupture(interactive=False):
xp0 = np.array([-90.898000])
xp1 = np.array([-91.308000])
yp0 = np.array([12.584000])
yp1 = np.array([12.832000])
zp = [0.0]
strike = azimuth(yp0[0], xp0[0], yp1[0], xp1[0])
origin = Origin({
'lat': 0.0,
'lon': 0.0,
'depth': 0.0,
'mag': 5.5,
'id': '',
'netid': 'abcd',
'network': '',
'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
interface_width = MAX_DEPTH / np.sin(np.radians(DIP))
widths = np.ones(xp0.shape) * interface_width
dips = np.ones(xp0.shape) * DIP
strike = [strike]
rupture = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
origin,
strike=strike)
plot_rupture_wire3d(rupture)
if interactive:
fname = os.path.join(os.path.expanduser('~'), 'rupture_wire_plot.png')
plt.savefig(fname)
print('Wire 3D plot saved to %s. Delete this file if you wish.' %
fname)
def test_map_rupture(interactive=False):
xp0 = np.array([-90.898000])
xp1 = np.array([-91.308000])
yp0 = np.array([12.584000])
yp1 = np.array([12.832000])
zp = [0.0]
strike = azimuth(yp0[0], xp0[0], yp1[0], xp1[0])
origin = Origin({'lat': 0.0,
'lon': 0.0,
'depth': 0.0,
'mag': 5.5,
'eventsourcecode': 'abcd'})
interface_width = MAX_DEPTH / np.sin(np.radians(DIP))
widths = np.ones(xp0.shape) * interface_width
dips = np.ones(xp0.shape) * DIP
strike = [strike]
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths, dips, origin, strike=strike)
map_rupture(rupture)
if interactive:
fname = os.path.join(os.path.expanduser('~'), 'rupture_map.png')
plt.savefig(fname)
print('Rupture map plot saved to %s. Delete this file if you wish.'
% fname)
def test_multisegment_discordant():
# The one thing that isn't check above is discordancy for segments
# with multiple quads. For this, we need a synthetic example.
x0 = np.array([0, 1, -1, 10, 9, 7])
y0 = np.array([0, 10, 20, 40, 35, 30])
z0 = np.array([0, 0, 0, 0, 0, 0])
x1 = np.array([1, -1, 0, 9, 7, 6])
y1 = np.array([10, 20, 30, 35, 30, 25])
z1 = np.array([0, 0, 0, 0, 0, 0])
x2 = np.array([3, 1, 2, 7, 5, 4])
y2 = np.array([10, 20, 30, 35, 30, 25])
z2 = np.array([10, 10, 10, 10, 10, 10])
x3 = np.array([2, 3, 1, 8, 7, 5])
y3 = np.array([0, 10, 20, 40, 35, 30])
z3 = np.array([10, 10, 10, 10, 10, 10])
epilat = 32.15270
epilon = -115.30500
proj = geo.utils.get_orthographic_projection(
epilon - 1, epilon + 1, epilat + 1, epilat - 1)
lon0, lat0 = proj(x0, y0, reverse=True)
lon1, lat1 = proj(x1, y1, reverse=True)
lon2, lat2 = proj(x2, y2, reverse=True)
lon3, lat3 = proj(x3, y3, reverse=True)
# Make an Origin object; most of the 'event' values don't matter for
# this example
origin = Origin({'lat': 0, 'lon': 0, 'depth': 0, 'mag': 7.2, 'eventsourcecode': ''})
rup = QuadRupture.fromVertices(
lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3,
origin, group_index=[0, 0, 0, 1, 1, 1])
# Sites
buf = 0.25
lat = np.linspace(np.nanmin(rup.lats) - buf, np.nanmax(rup.lats) + buf, 20)
lon = np.linspace(np.nanmin(rup.lons) - buf, np.nanmax(rup.lons) + buf, 20)
lons, lats = np.meshgrid(lon, lat)
dep = np.zeros_like(lons)
x, y = proj(lon, lat)
rupx, rupy = proj(rup.lons, rup.lats)
# Calculate U and T
dtypes = ['U', 'T']
dists = get_distance(dtypes, lats, lons, dep, rup)
targetU = np.array(
[[-28.53228275, -28.36479713, -28.20139732, -28.0407734,
-27.88135558, -27.72144153, -27.55935946, -27.39362017,
-27.22300147, -27.04653062, -26.86338215, -26.67275638,
-26.47381287, -26.26569449, -26.04762427, -25.81902477,
-25.57961136, -25.32943282, -25.06885791, -24.79852214],
[-23.53750292, -23.3748086, -23.21793537, -23.06521934,
-22.91449689, -22.76331684, -22.60928211, -22.45042208,
-22.28542121, -22.11355532, -21.93435402, -21.74720475,
-21.55115107, -21.34497916, -21.12749377, -20.89781118,
-20.6555466, -20.40086149, -20.13439948, -19.85716145],
[-18.53499939, -18.37689929, -18.22732841, -18.08427516,
-17.94468687, -17.80472632, -17.66045115, -17.50880802,
-17.3484421, -17.17963435, -17.0032098, -16.81921732,
-16.62638972, -16.42258419, -16.20564846, -15.9741218,
-15.72753538, -15.4663671, -15.19180844, -14.9054813],
[-13.52283359, -13.36797542, -13.22589288, -13.09466537,
-12.97028551, -12.84653536, -12.71591089, -12.57212088,
-12.41335561, -12.24319318, -12.06681006, -11.88598424,
-11.69798166, -11.49796348, -11.28169605, -11.04691388,
-10.79343174, -10.52262594, -10.23677602, -9.93851158],
[-8.49936685, -8.34357094, -8.20650964, -8.08786858,
-7.98403171, -7.88628837, -7.78005273, -7.64833307,
-7.48359988, -7.29992491, -7.11862682, -6.94410189,
-6.76618701, -6.5727842, -6.35634881, -6.11465447,
-5.84925708, -5.56369035, -5.26212482, -4.94857454],
[-3.46638168, -3.30047216, -3.15914418, -3.04618465,
-2.96252939, -2.90194067, -2.84436315, -2.75029014,
-2.56983592, -2.33744275, -2.1512136, -1.99833104,
-1.84066354, -1.6541107, -1.43071517, -1.17252753,
-0.88592286, -0.57817222, -0.25582315, 0.07585567],
[1.56416954, 1.75393848, 1.9183586, 2.04909316,
2.13723278, 2.17776584, 2.18272501, 2.20967639,
2.37405656, 2.65073289, 2.80205222, 2.90973407,
3.05124404, 3.2505182, 3.50336116, 3.7967575,
4.11742779, 4.45465822, 4.80070204, 5.15033407],
[6.5633489, 6.78740885, 6.99419348, 7.17551069,
7.31963558, 7.4113505, 7.43666779, 7.40177458,
7.40517136, 7.58520044, 7.62013169, 7.71596777,
7.90558457, 8.17213015, 8.49008681, 8.83763176,
9.19937294, 9.56556659, 9.9305469, 10.29132309],
[11.48996073, 11.74301446, 11.99016964, 12.22782156,
12.44984059, 12.6446727, 12.78798484, 12.82584849,
12.61992833, 12.26579742, 12.32166685, 12.54665462,
12.86628045, 13.23578462, 13.62571822, 14.01882924,
14.40617707, 14.78388296, 15.15089889, 15.5076165],
[16.31383216, 16.57376544, 16.83189511, 17.08626411,
17.33309437, 17.56429108, 17.76005623, 17.85853532,
17.57101025, 17.32637346, 17.45075419, 17.77199513,
18.16933168, 18.58284635, 18.9891851, 19.37985879,
19.75324557, 20.11079653, 20.4549905, 20.78837053],
[21.03975749, 21.28450315, 21.5243142, 21.75603974,
21.97469496, 22.17298057, 22.34310053, 22.49668569,
22.73940191, 22.70030633, 22.95351405, 23.35967832,
23.75891016, 24.14867803, 24.51536915, 24.85878249,
25.18398203, 25.49615514, 25.79932964, 26.09638269],
[25.70484089, 25.92709225, 26.14280395, 26.35119497,
26.55363501, 26.75827099, 26.9915523, 27.31779086,
27.77993211, 27.71070831, 28.13624949, 28.723482,
29.25285078, 29.66404032, 30.00169474, 30.30044315,
30.57916576, 30.84804427, 31.1126134, 31.37586841],
[30.35406633, 30.5585145, 30.75843356, 30.95627127,
31.15811912, 31.3763124, 31.63114968, 31.94156189,
32.23691802, 32.38759301, 32.86915665, 33.83467935,
34.46125278, 34.89905345, 35.25111257, 35.55095664,
35.82150686, 36.07720619, 36.32643896, 36.57385362],
[35.0222379, 35.21734711, 35.41081942, 35.60589495,
35.80774808, 36.02313791, 36.25826988, 36.51619168,
36.81025966, 37.21777129, 37.86674108, 38.66578072,
39.25203723, 39.78060643, 40.20815617, 40.5606039,
40.86634527, 41.14457482, 41.40732554, 41.66197722],
[39.73046099, 39.92514041, 40.12152415, 40.32316112,
40.5350467, 40.76393316, 41.01937758, 41.3172128,
41.68596492, 42.16604148, 42.77622755, 43.447503,
44.03771478, 44.55012468, 45.00551259, 45.40376857,
45.75505135, 46.07204699, 46.36554362, 46.64361367],
[44.4876174, 44.68959464, 44.89710008, 45.11420443,
45.34646809, 45.60143197, 45.88932906, 46.22363997,
46.61975585, 47.0884227, 47.62307543, 48.1913408,
48.74937117, 49.26945799, 49.74327902, 50.17123158,
50.55810895, 50.91098842, 51.23731582, 51.54375617],
[49.29279265, 49.50696882, 49.73006999, 49.96625305,
50.22080319, 50.50022572, 50.81209441, 51.1642666,
51.56290694, 52.00913021, 52.49553006, 53.00565389,
53.51861282, 54.01614414, 54.48672101, 54.9254339,
55.33212663, 55.70951516, 56.06170563, 56.39317058],
[54.13906629, 54.3671694, 54.60643024, 54.86053563,
55.13377911, 55.43088558, 55.75658576, 56.1148189,
56.50752978, 56.93329478, 57.38640012, 57.85715119,
58.33367994, 58.80451404, 59.26065475, 59.69644542,
60.10938419, 60.49940252, 60.86803179, 61.21767916],
[59.01741908, 59.25887491, 59.51248349, 59.78119592,
60.06816694, 60.37651862, 60.70895927, 61.0672529,
61.45160192, 61.86010542, 62.28853397, 62.73062937,
63.17894547, 63.62598375, 64.06523791, 64.49185106,
64.90281064, 65.2967858, 65.67377362, 66.03469546],
[63.9193099, 64.17236414, 64.4376317, 64.71732366,
65.01362255, 65.32847988, 65.66334836, 66.0188704,
66.39457546, 66.7886684, 67.19800022, 67.61828012,
68.04451487, 68.47157851, 68.89476917, 69.31022713,
69.71515194, 70.10782673, 70.4875021, 70.85420436]]
)
np.testing.assert_allclose(targetU, dists['U'], atol=0.01)
targetT = np.array(
[[-2.27427469e+01, -1.97498544e+01, -1.67512900e+01,
-1.37464632e+01, -1.07350712e+01, -7.71715083e+00,
-4.69305811e+00, -1.66336318e+00, 1.37131605e+00,
4.41047613e+00, 7.45381136e+00, 1.05011799e+01,
1.35524779e+01, 1.66074913e+01, 1.96657949e+01,
2.27267294e+01, 2.57894503e+01, 2.88530154e+01,
3.19164798e+01, 3.49789747e+01],
[-2.30778766e+01, -2.00896906e+01, -1.70950973e+01,
-1.40931667e+01, -1.10834219e+01, -8.06600712e+00,
-5.04171582e+00, -2.01179123e+00, 1.02248614e+00,
4.06025218e+00, 7.10129626e+00, 1.01459367e+01,
1.31946312e+01, 1.62475702e+01, 1.93044511e+01,
2.23644788e+01, 2.54265185e+01, 2.84892997e+01,
3.15515954e+01, 3.46123426e+01],
[-2.33971472e+01, -2.04144525e+01, -1.74245193e+01,
-1.44256870e+01, -1.14169177e+01, -8.39830615e+00,
-5.37141115e+00, -2.33902937e+00, 6.95823925e-01,
3.73133431e+00, 6.76769593e+00, 9.80663091e+00,
1.28500821e+01, 1.58991008e+01, 1.89534737e+01,
2.20119662e+01, 2.50728111e+01, 2.81341606e+01,
3.11943854e+01, 3.42522163e+01],
[-2.36965870e+01, -2.07206976e+01, -1.77370901e+01,
-1.47426715e+01, -1.17347885e+01, -8.71247709e+00,
-5.67801094e+00, -2.63761285e+00, 4.00625914e-01,
3.43182302e+00, 6.45782532e+00, 9.48491128e+00,
1.25187545e+01, 1.55616657e+01, 1.86127822e+01,
2.16694756e+01, 2.47286680e+01, 2.77876297e+01,
3.08443066e+01, 3.38973527e+01],
[-2.39698399e+01, -2.10022612e+01, -1.80281475e+01,
-1.50423801e+01, -1.20388157e+01, -9.01204040e+00,
-5.96160398e+00, -2.89867328e+00, 1.52194374e-01,
3.17268218e+00, 6.17334725e+00, 9.17699572e+00,
1.21964990e+01, 1.52330975e+01, 1.82821226e+01,
2.13375815e+01, 2.43943933e+01, 2.74490375e+01,
3.04994435e+01, 3.35446330e+01],
[-2.42070742e+01, -2.12471979e+01, -1.82855675e+01,
-1.53163304e+01, -1.23296744e+01, -9.31127857e+00,
-6.24535210e+00, -3.12882361e+00, -2.24460581e-02,
2.95354485e+00, 5.89215412e+00, 8.86387424e+00,
1.18748249e+01, 1.49128245e+01, 1.79640055e+01,
2.10182501e+01, 2.40696313e+01, 2.71153177e+01,
3.01543919e+01, 3.31869788e+01],
[-2.43971375e+01, -2.14368866e+01, -1.84826148e+01,
-1.55321207e+01, -1.25786621e+01, -9.60654678e+00,
-6.58612151e+00, -3.48118311e+00, -3.16555025e-01,
2.61618307e+00, 5.53740540e+00, 8.52666510e+00,
1.15623361e+01, 1.46149780e+01, 1.76674294e+01,
2.07125025e+01, 2.37483764e+01, 2.67756033e+01,
2.97955606e+01, 3.28097430e+01],
[-2.45384925e+01, -2.15583842e+01, -1.85874288e+01,
-1.56290738e+01, -1.26867853e+01, -9.76140655e+00,
-6.84407754e+00, -3.90089971e+00, -8.41806596e-01,
2.14754495e+00, 5.18583472e+00, 8.26271822e+00,
1.13266091e+01, 1.43684333e+01, 1.73916223e+01,
2.04017469e+01, 2.34034936e+01, 2.64002111e+01,
2.93941282e+01, 3.23866586e+01],
[-2.46576775e+01, -2.16355610e+01, -1.86129545e+01,
-1.55919156e+01, -1.25763765e+01, -9.57306672e+00,
-6.59044329e+00, -3.62352541e+00, -5.92041388e-01,
2.33255341e+00, 5.29498494e+00, 8.24834463e+00,
1.11833819e+01, 1.41167617e+01, 1.70571082e+01,
2.00065102e+01, 2.29645946e+01, 2.59302937e+01,
2.89023967e+01, 3.18797332e+01],
[-2.48161623e+01, -2.17489533e+01, -1.86651328e+01,
-1.55589864e+01, -1.24224388e+01, -9.24466730e+00,
-6.01521475e+00, -2.75148770e+00, 3.89519039e-01,
2.99589525e+00, 5.45696689e+00, 8.01247078e+00,
1.07291540e+01, 1.35565782e+01, 1.64461360e+01,
1.93723515e+01, 2.23222250e+01, 2.52881249e+01,
2.82650171e+01, 3.12494172e+01],
[-2.50857405e+01, -2.20002811e+01, -1.88926336e+01,
-1.57550887e+01, -1.25770789e+01, -9.34497451e+00,
-6.04430316e+00, -2.67290100e+00, 5.40854953e-01,
2.30509492e+00, 3.58183843e+00, 6.23701436e+00,
9.28727128e+00, 1.23205706e+01, 1.53428945e+01,
1.83666035e+01, 2.13934954e+01, 2.44218171e+01,
2.74496472e+01, 3.04757209e+01],
[-2.55082697e+01, -2.24454912e+01, -1.93710045e+01,
-1.62824768e+01, -1.31767102e+01, -1.00469827e+01,
-6.86985653e+00, -3.54681638e+00, 1.07062999e-01,
3.34891657e-01, -1.70694750e-01, 3.57896940e+00,
7.17013928e+00, 1.05232789e+01, 1.37976070e+01,
1.70230221e+01, 2.02076136e+01, 2.33576919e+01,
2.64794914e+01, 2.95785985e+01],
[-2.60778515e+01, -2.30695744e+01, -2.00684150e+01,
-1.70790651e+01, -1.41074315e+01, -1.11587507e+01,
-8.23273307e+00, -5.33306966e+00, -2.80144302e+00,
-1.84760416e+00, -1.05368779e+00, 1.26163211e+00,
4.90086292e+00, 8.53883059e+00, 1.20996577e+01,
1.55589098e+01, 1.89237978e+01, 2.22114952e+01,
2.54390313e+01, 2.86203790e+01],
[-2.67537229e+01, -2.38123298e+01, -2.08964272e+01,
-1.80168638e+01, -1.51896230e+01, -1.24401995e+01,
-9.81536176e+00, -7.41008520e+00, -5.38073414e+00,
-3.78262975e+00, -2.29669890e+00, -3.53057240e-01,
3.13642477e+00, 6.97021789e+00, 1.07026969e+01,
1.42945488e+01, 1.77655640e+01, 2.11406146e+01,
2.44409375e+01, 2.76832489e+01],
[-2.74832153e+01, -2.46028623e+01, -2.17593854e+01,
-1.89653378e+01, -1.62381218e+01, -1.36022404e+01,
-1.10914555e+01, -8.74572618e+00, -6.58963863e+00,
-4.58336507e+00, -2.57607747e+00, -2.67233150e-01,
2.82788692e+00, 6.36737407e+00, 9.93334021e+00,
1.34440609e+01, 1.68846862e+01, 2.02577163e+01,
2.35710668e+01, 2.68337230e+01],
[-2.82199728e+01, -2.53838486e+01, -2.25869234e+01,
-1.98388981e+01, -1.71512612e+01, -1.45365893e+01,
-1.20059297e+01, -9.56220853e+00, -7.18799023e+00,
-4.83006994e+00, -2.39120744e+00, 2.51308627e-01,
3.17331949e+00, 6.33022626e+00, 9.61428455e+00,
1.29426788e+01, 1.62705993e+01, 1.95770961e+01,
2.28539081e+01, 2.60992146e+01],
[-2.89332200e+01, -2.61222251e+01, -2.33461951e+01,
-2.06105222e+01, -1.79200485e+01, -1.52776479e+01,
-1.26817390e+01, -1.01225741e+01, -7.57801870e+00,
-5.01122873e+00, -2.37434916e+00, 3.78303328e-01,
3.27093827e+00, 6.29527723e+00, 9.41912399e+00,
1.26046423e+01, 1.58204753e+01, 1.90448689e+01,
2.22643265e+01, 2.54712657e+01],
[-2.96082809e+01, -2.68067500e+01, -2.40331802e+01,
-2.12894659e+01, -1.85760763e+01, -1.58910124e+01,
-1.32284735e+01, -1.05774862e+01, -7.92111801e+00,
-5.23724922e+00, -2.50179068e+00, 3.05790568e-01,
3.19666197e+00, 6.16975035e+00, 9.21353475e+00,
1.23109519e+01, 1.54443017e+01, 1.85982825e+01,
2.17611016e+01, 2.49243957e+01],
[-3.02420504e+01, -2.74395034e+01, -2.46578094e+01,
-2.18967353e+01, -1.91546206e+01, -1.64278219e+01,
-1.37101816e+01, -1.09927140e+01, -8.26378719e+00,
-5.51007519e+00, -2.71836365e+00, 1.22111758e-01,
3.01754598e+00, 5.96851903e+00, 8.97043180e+00,
1.20150997e+01, 1.50927299e+01, 1.81935916e+01,
2.13090724e+01, 2.44321477e+01],
[-3.08377073e+01, -2.80281994e+01, -2.52335334e+01,
-2.24524366e+01, -1.96825082e+01, -1.69199811e+01,
-1.41595768e+01, -1.13945492e+01, -8.61701306e+00,
-5.81861191e+00, -2.99148017e+00, -1.29317230e-01,
2.77170749e+00, 5.71249079e+00, 8.69110042e+00,
1.17033684e+01, 1.47437429e+01, 1.78061436e+01,
2.08846464e+01, 2.39739290e+01]]
)
np.testing.assert_allclose(targetT, dists['T'], atol=0.01)
def test_rupture_depth(interactive=False):
DIP = 17.0
WIDTH = 20.0
GRIDRES = 0.1
names = ['single', 'double', 'triple',
'concave', 'concave_simple', 'ANrvSA']
means = [3.1554422780092461, 2.9224454569459781,
3.0381968625073563, 2.0522694624400271,
2.4805390352818755, 2.8740121776209673]
stds = [2.1895293825074575, 2.0506459673526174,
2.0244588429154402, 2.0112565876976416,
2.1599789955270019, 1.6156220309120068]
xp0list = [np.array([118.3]),
np.array([10.1, 10.1]),
np.array([10.1, 10.1, 10.3]),
np.array([10.9, 10.5, 10.9]),
np.array([10.9, 10.6]),
np.array([-76.483, -76.626, -76.757, -76.99, -77.024, -76.925,
-76.65, -76.321, -75.997, -75.958])]
xp1list = [np.array([118.3]),
np.array([10.1, 10.3]),
np.array([10.1, 10.3, 10.1]),
np.array([10.5, 10.9, 11.3]),
np.array([10.6, 10.9]),
np.array([-76.626, -76.757, -76.99, -77.024, -76.925, -76.65,
-76.321, -75.997, -75.958, -76.006])]
yp0list = [np.array([34.2]),
np.array([34.2, 34.5]),
np.array([34.2, 34.5, 34.8]),
np.array([34.2, 34.5, 34.8]),
np.array([35.1, 35.2]),
np.array([-52.068, -51.377, -50.729, -49.845, -49.192, -48.507,
-47.875, -47.478, -47.08, -46.422])]
yp1list = [np.array([34.5]),
np.array([34.5, 34.8]),
np.array([34.5, 34.8, 35.1]),
np.array([34.5, 34.8, 34.6]),
np.array([35.2, 35.4]),
np.array([-51.377, -50.729, -49.845, -49.192, -48.507, -47.875,
-47.478, -47.08, -46.422, -45.659])]
for i in range(0, len(xp0list)):
xp0 = xp0list[i]
xp1 = xp1list[i]
yp0 = yp0list[i]
yp1 = yp1list[i]
name = names[i]
mean_value = means[i]
std_value = stds[i]
zp = np.zeros(xp0.shape)
strike = azimuth(xp0[0], yp0[0], xp1[-1], yp1[-1])
widths = np.ones(xp0.shape) * WIDTH
dips = np.ones(xp0.shape) * DIP
strike = [strike]
origin = Origin({'id': 'test',
'lon': 0, 'lat': 0,
'depth': 5.0, 'mag': 7.0, 'netid': 'us',
'network': '', 'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())})
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths, dips, origin, strike=strike)
# make a grid of points over both quads, ask for depths
ymin = np.nanmin(rupture.lats)
ymax = np.nanmax(rupture.lats)
xmin = np.nanmin(rupture.lons)
xmax = np.nanmax(rupture.lons)
xmin = np.floor(xmin * (1 / GRIDRES)) / (1 / GRIDRES)
xmax = np.ceil(xmax * (1 / GRIDRES)) / (1 / GRIDRES)
ymin = np.floor(ymin * (1 / GRIDRES)) / (1 / GRIDRES)
ymax = np.ceil(ymax * (1 / GRIDRES)) / (1 / GRIDRES)
geodict = GeoDict.createDictFromBox(
xmin, xmax, ymin, ymax, GRIDRES, GRIDRES)
nx = geodict.nx
ny = geodict.ny
depths = np.zeros((ny, nx))
for row in range(0, ny):
for col in range(0, nx):
lat, lon = geodict.getLatLon(row, col)
depth = rupture.getDepthAtPoint(lat, lon)
depths[row, col] = depth
np.testing.assert_almost_equal(np.nanmean(depths), mean_value)
np.testing.assert_almost_equal(np.nanstd(depths), std_value)
if interactive:
fig, axes = plt.subplots(nrows=2, ncols=1)
ax1, ax2 = axes
xdata = np.append(xp0, xp1[-1])
ydata = np.append(yp0, yp1[-1])
plt.sca(ax1)
plt.plot(xdata, ydata, 'b')
plt.sca(ax2)
im = plt.imshow(depths, cmap='viridis_r') # noqa
ch = plt.colorbar() # noqa
fname = os.path.join(os.path.expanduser('~'),
'quad_%s_test.png' % name)
print('Saving image for %s quad test... %s' % (name, fname))
plt.savefig(fname)
plt.close()
def test_EdgeRupture():
# Rupture requires an origin even when not used:
origin = Origin({'id': 'test',
'lon': 0, 'lat': 0,
'depth': 5.0, 'mag': 7.0, 'netid': 'us',
'network': '', 'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())})
file = os.path.join(homedir, 'rupture_data/cascadia.json')
rup = get_rupture(origin, file)
np.testing.assert_allclose(rup.getArea(), 105635.92827547337)
# Force read Northridge as EdgeRupture
file = os.path.join(homedir, 'rupture_data/northridge_fault.txt')
d = text_to_json(file, new_format=True)
rupt = EdgeRupture(d, origin)
strike = rupt.getStrike()
np.testing.assert_allclose(strike, 121.97, atol=0.01)
dip = rupt.getDip()
np.testing.assert_allclose(dip, 40.12, atol=0.01)
L = rupt.getLength()
np.testing.assert_allclose(L, 17.99, atol=0.01)
W = rupt.getWidth()
np.testing.assert_allclose(W, 23.92, atol=0.01)
ztor = rupt.getDepthToTop()
np.testing.assert_allclose(ztor, 5, atol=0.01)
# And again for the same vertices but reversed order
file = os.path.join(homedir, 'rupture_data/northridge_fixed_fault.txt')
d = text_to_json(file, new_format=True)
rupt = EdgeRupture(d, origin)
strike = rupt.getStrike()
np.testing.assert_allclose(strike, 121.97, atol=0.01)
dip = rupt.getDip()
np.testing.assert_allclose(dip, 40.12, atol=0.01)
L = rupt.getLength()
np.testing.assert_allclose(L, 17.99, atol=0.01)
W = rupt.getWidth()
np.testing.assert_allclose(W, 23.92, atol=0.01)
ztor = rupt.getDepthToTop()
np.testing.assert_allclose(ztor, 5, atol=0.01)
# Test for fromArrays method
toplats = np.array([37.0, 38.0])
toplons = np.array([-120.0, -120.0])
topdeps = np.array([0.0, 0.0])
botlats = copy.copy(toplats)
botlons = copy.copy(toplons)
botdeps = np.array([10.0, 10.0])
erup = EdgeRupture.fromArrays(toplons, toplats, topdeps, botlons, botlats,
botdeps, origin)
# Error: array lengths differ
with pytest.raises(ShakeLibException) as e:
qrup = QuadRupture.fromVertices(
[toplons[0]], [toplats[0]], [topdeps[0]],
[toplons[1]], [toplats[1]], [topdeps[1]],
[botlons[1]], [botlats[1]], [botdeps[1]],
[botlons[0]], [botlats[0]], [botdeps[0]][:-1],
origin)
print(str(e))
# Error: group index too long
with pytest.raises(ShakeLibException) as e:
qrup = QuadRupture.fromVertices(
[toplons[0]], [toplats[0]], [topdeps[0]],
[toplons[1]], [toplats[1]], [topdeps[1]],
[botlons[1]], [botlats[1]], [botdeps[1]],
[botlons[0]], [botlats[0]], [botdeps[0]],
origin, group_index=[0, 0, 0, 0, 0, 0])
print(str(e))
qrup = QuadRupture.fromVertices(
[toplons[0]], [toplats[0]], [topdeps[0]],
[toplons[1]], [toplats[1]], [topdeps[1]],
[botlons[1]], [botlats[1]], [botdeps[1]],
[botlons[0]], [botlats[0]], [botdeps[0]],
origin)
np.testing.assert_allclose(erup.getArea(), 1108.9414759967776)
np.testing.assert_allclose(erup.getDepthToTop(), 0)
np.testing.assert_allclose(erup.getLength(), 111.19492664455889)
np.testing.assert_allclose(
erup.lats, np.array([37., 38., 38., 37., 37., np.nan]))
np.testing.assert_allclose(
erup.lons, np.array([-120., -120., -120., -120., -120., np.nan]))
np.testing.assert_allclose(
erup.depths, np.array([0., 0., 10., 10., 0., np.nan]))
np.testing.assert_allclose(
erup._getGroupIndex(), np.array([0., 0.]))
quads = erup.getQuadrilaterals()
np.testing.assert_allclose(quads[0][0].x, -120.0)
# Need to also test the distances with EdgeRupture
lons = np.linspace(-120.1, -121.0, 10)
lats = np.linspace(37.0, 38, 10)
deps = np.zeros_like(lons)
rrup1, _ = qrup.computeRrup(lons, lats, deps)
rrup2, _ = erup.computeRrup(lons, lats, deps)
np.testing.assert_allclose(rrup1, rrup2, atol=2e-2)
rjb1, _ = qrup.computeRjb(lons, lats, deps)
rjb2, _ = erup.computeRjb(lons, lats, deps)
np.testing.assert_allclose(rjb1, rjb2, atol=2e-2)
gc2 = erup.computeGC2(lons, lats, deps)
targetRy0 = np.array(
[0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.67335931])
targetRx = np.array(
[-8.88024949, -17.73390996, -26.56167797, -35.3634266,
-44.13902929, -52.88835984, -61.61129242, -70.30770154,
-78.97746209, -87.6204493])
np.testing.assert_allclose(gc2['ry0'], targetRy0)
np.testing.assert_allclose(gc2['rx'], targetRx)
def test_fromOrientation():
py = [0, 0.5]
px = [0, 0.5]
pz = [10, 20]
dx = [5, 7]
dy = [8, 5]
width = [10, 40]
length = [20, 50]
strike = [0, 90]
dip = [30, 20]
# Rupture requires an origin even when not used:
origin = Origin({'id': 'test',
'lon': 0, 'lat': 0,
'depth': 5.0, 'mag': 7.0, 'netid': 'us',
'network': '', 'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())})
rupture = QuadRupture.fromOrientation(px, py, pz, dx, dy, length, width,
strike, dip, origin)
p1 = rupture._geojson['features'][0]['geometry']['coordinates'][0][0][0]
p2 = rupture._geojson['features'][0]['geometry']['coordinates'][0][0][1]
p3 = rupture._geojson['features'][0]['geometry']['coordinates'][0][0][2]
p4 = rupture._geojson['features'][0]['geometry']['coordinates'][0][0][3]
p5 = rupture._geojson['features'][0]['geometry']['coordinates'][0][1][0]
p6 = rupture._geojson['features'][0]['geometry']['coordinates'][0][1][1]
p7 = rupture._geojson['features'][0]['geometry']['coordinates'][0][1][2]
p8 = rupture._geojson['features'][0]['geometry']['coordinates'][0][1][3]
# Check depths
np.testing.assert_allclose(p1[2], 6)
np.testing.assert_allclose(p2[2], 6)
np.testing.assert_allclose(p3[2], 11)
np.testing.assert_allclose(p4[2], 11)
np.testing.assert_allclose(p5[2], 18.2898992834)
np.testing.assert_allclose(p6[2], 18.2898992834)
np.testing.assert_allclose(p7[2], 31.9707050164)
np.testing.assert_allclose(p8[2], 31.9707050164)
# Exception raised if no origin
with pytest.raises(Exception) as a:
rupture = QuadRupture.fromOrientation(px, py, pz, dx, dy, length,
width, strike, dip, None)
print(str(a))
# Exception raised if different lengths of arrays
with pytest.raises(Exception) as a:
py = [0, 2]
px = [0]
pz = [10]
dx = [5]
dy = [8]
width = [10]
length = [20]
strike = [0]
dip = [30]
origin = Origin({'id': 'test',
'lon': 0, 'lat': 0,
'depth': 5.0, 'mag': 7.0, 'netid': 'us',
'network': '', 'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())})
rupture = QuadRupture.fromOrientation(px, py, pz, dx, dy, length,
width, strike, dip, origin)
print(str(a))
def test_fromTrace():
xp0 = [0.0]
xp1 = [0.0]
yp0 = [0.0]
yp1 = [0.05]
zp = [0.0]
widths = [10.0]
dips = [45.0]
# Rupture requires an origin even when not used:
origin = Origin({
'id': 'test',
'lon': -121.81529, 'lat': 37.73707,
'depth': 5.0, 'mag': 7.0, 'netid': 'us',
'network': '', 'locstring': '',
'time': HistoricTime.utcfromtimestamp(time.time())
})
# Error: unequal array lengths
with pytest.raises(ShakeLibException) as e:
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp[:-1], widths,
dips, origin,
reference='From J Smith, (personal communication)')
print(str(e))
# Error: invalid strike
with pytest.raises(ShakeLibException) as e:
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths,
dips, origin, strike=[236.0, 250.0],
reference='From J Smith, (personal communication)')
print(str(e))
# TODO: These write tests exercise code, but we don't check the results
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths,
dips, origin,
reference='From J Smith, (personal communication)')
fstr = io.StringIO()
rupture.writeTextFile(fstr)
tfile = tempfile.NamedTemporaryFile()
tname = tfile.name
tfile.close()
rupture.writeTextFile(tname)
os.remove(tname)
tfile = tempfile.NamedTemporaryFile()
tname = tfile.name
tfile.close()
rupture.writeGeoJson(tname)
os.remove(tname)
xp0 = [-121.81529, -121.82298]
xp1 = [-121.82298, -121.83068]
yp0 = [37.73707, 37.74233]
yp1 = [37.74233, 37.74758]
zp = [10, 15]
widths = [15.0, 20.0]
dips = [30.0, 45.0]
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths,
dips, origin,
reference='From J Smith, (personal communication)')
assert rupture.getReference() == 'From J Smith, (personal communication)'
rorigin = rupture.getOrigin()
assert rorigin.id == origin.id
assert rorigin.mag == origin.mag
assert rorigin.depth == origin.depth
rx = rupture.getRuptureContext([])
np.testing.assert_allclose([rx.strike, rx.dip, rx.ztor, rx.width],
[-49.183708644954905, 37.638322472702534,
9.999999999371358, 17.47024205615428])
rhyp = rupture.computeRhyp(np.array([-121.5]), np.array([37.0]),
np.array([0]))
repi = rupture.computeRepi(np.array([-121.5]), np.array([37.0]),
np.array([0]))
np.testing.assert_allclose([rhyp[0], repi[0]], [86.709236, 86.564956])
def parse_bssc2014_ucerf(rupts, args):
"""
This function is to parse the UCERF3 json file format. The ruptures in
UCERF3 are very complex and so we don't exepct to get other rupture lists
in this format.
Args:
rupts (dict): Python translation of rupture json file using json.load
method.
args (ArgumentParser): argparse object.
Returns:
dict: Dictionary of rupture information.
"""
rlist = []
nrup = len(rupts['events'])
if args.index is not None:
iter = args.index
iter = map(int, iter)
else:
iter = range(nrup)
for i in iter:
event_name = rupts['events'][i]['name']
short_name = event_name.split('EllB')[0].split('Shaw09')[0].split(
'2011')[0].split('HB08')[0].rstrip()
magnitude = rupts['events'][i]['magnitude']
rake = rupts['events'][i]['rake']
sections = np.array(rupts['events'][i]['sections'])
nsections = len(sections)
secind = 0
new_seg_ind = []
rev = np.array([[]])
xp0 = np.array([[]])
xp1 = np.array([[]])
yp0 = np.array([[]])
yp1 = np.array([[]])
zp = np.array([[]])
dip_sec = np.array([[]])
strike_sec = np.array([[]])
width_sec = np.array([[]])
for j in range(0, nsections):
trace_sec = np.array(sections[j]['resampledTrace'])
top_sec_lon = trace_sec[:, 0]
top_sec_lat = trace_sec[:, 1]
top_sec_z = trace_sec[:, 2]
n_sec_trace = len(trace_sec) - 1
dip_sec = np.append(dip_sec,
np.repeat(sections[j]['dip'], n_sec_trace))
dipDir_sec = np.repeat(sections[j]['dipDir'], n_sec_trace)
strike_sec = np.append(strike_sec, dipDir_sec - 90)
width_sec = np.append(width_sec,
np.repeat(sections[j]['width'], n_sec_trace))
rev_sec = sections[j]['reversed']
rev = np.append(rev, np.repeat(rev_sec, n_sec_trace))
xp0_sec = top_sec_lon[range(0, n_sec_trace)]
xp1_sec = top_sec_lon[range(1, n_sec_trace + 1)]
yp0_sec = top_sec_lat[range(0, n_sec_trace)]
yp1_sec = top_sec_lat[range(1, n_sec_trace + 1)]
zp_sec = top_sec_z[range(0, n_sec_trace)]
if rev_sec is False:
xp0 = np.append(xp0, xp0_sec)
xp1 = np.append(xp1, xp1_sec)
yp0 = np.append(yp0, yp0_sec)
yp1 = np.append(yp1, yp1_sec)
zp = np.append(zp, zp_sec)
else:
xp0 = np.append(xp0, xp1_sec[::-1])
xp1 = np.append(xp1, xp0_sec[::-1])
yp0 = np.append(yp0, yp1_sec[::-1])
yp1 = np.append(yp1, yp0_sec[::-1])
zp = np.append(zp, zp_sec[::-1])
new_seg_ind.extend([secind] * n_sec_trace)
secind = secind + 1
# Origin
origin = Origin({'mag': 0, 'id': '', 'lat': 0, 'lon': 0, 'depth': 0})
rupt = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
width_sec,
dip_sec,
origin,
strike=strike_sec,
group_index=new_seg_ind,
reference=args.reference)
quads = rupt.getQuadrilaterals()
edges = get_rupture_edges(quads, rev)
hlat, hlon, hdepth = get_hypo(edges, args)
id_str, eventsourcecode, real_desc = get_event_id(
event_name, magnitude, args.directivity, args.dirind, quads)
event = {
'lat': hlat,
'lon': hlon,
'depth': hdepth,
'mag': magnitude,
'rake': rake,
'id': id_str,
'locstring': event_name,
'type': 'ALL',
'timezone': 'UTC',
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'created': ShakeDateTime.utcfromtimestamp(int(time.time()))
}
# Update rupture with new origin info
origin = Origin(event)
rupt = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
width_sec,
dip_sec,
origin,
strike=strike_sec,
group_index=new_seg_ind,
reference=args.reference)
rdict = {
'rupture': rupt,
'event': event,
'edges': edges,
'id_str': id_str,
'short_name': short_name,
'real_desc': real_desc,
'eventsourcecode': eventsourcecode
}
rlist.append(rdict)
return rlist
def test_rv4():
magnitude = 7.0
rake = 90.0
width = np.array([28])
rupx = np.array([0, 0])
rupy = np.array([0, 32])
zp = np.array([0])
dip = np.array([30])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
# Dummy Origin
origin = Origin({'lat': 0,
'lon': 0,
'depth': 0,
'mag': 0,
'eventsourcecode': 'rv4',
'rake': rake})
# Rupture
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='')
L = rup.getLength()
# Figure out epicenter
tmp = rup.getQuadrilaterals()[0]
pp0 = Vector.fromPoint(point.Point(
tmp[0].longitude, tmp[0].latitude, tmp[0].depth))
pp1 = Vector.fromPoint(point.Point(
tmp[1].longitude, tmp[1].latitude, tmp[1].depth))
pp2 = Vector.fromPoint(point.Point(
tmp[2].longitude, tmp[2].latitude, tmp[2].depth))
pp3 = Vector.fromPoint(point.Point(
tmp[3].longitude, tmp[3].latitude, tmp[3].depth))
dxp = 6 / L
dyp = (width - 8) / width
mp0 = pp0 + (pp1 - pp0) * dxp
mp1 = pp3 + (pp2 - pp3) * dxp
rp = mp0 + (mp1 - mp0) * dyp
epilat, epilon, epidepth = ecef2latlon(rp.x, rp.y, rp.z)
# Fix Origin:
origin = Origin({'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'eventsourcecode': 'rv4',
'rake': rake})
x = np.linspace(-50, 50, 11)
y = np.linspace(-50, 50, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=2.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.72143257e-03, 1.34977260e-03, 4.33616224e-15,
1.24446253e-03, 1.16142357e-03, 2.25464716e-03,
7.05281751e-04, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 7.62610242e-03,
1.25133844e-02, 5.61896104e-03, 7.63126014e-15,
4.52266194e-03, 4.67970900e-03, 1.02820316e-02,
5.13160096e-03, -6.13926251e-03],
[0.00000000e+00, 4.00495234e-03, 2.37608386e-02,
2.37139333e-02, 9.55224050e-03, 5.66364910e-15,
7.70344813e-03, 7.36466362e-03, 1.48239704e-02,
8.40388145e-03, -1.58592485e-02],
[8.08385547e-19, 9.38150101e-03, 3.38610620e-02,
3.85351492e-02, 1.91044918e-02, 3.98697802e-15,
1.54321666e-02, 1.21913760e-02, 2.04435166e-02,
1.04931859e-02, -1.85935894e-02],
[2.12025421e-18, 1.37316085e-02, 4.40193799e-02,
6.16562477e-02, 4.77612496e-02, 2.60257085e-15,
3.86322888e-02, 1.97965887e-02, 2.64882038e-02,
1.23335908e-02, -2.07389932e-02],
[2.64338576e-18, 1.45898292e-02, 4.89104213e-02,
7.70703166e-02, 9.55225258e-02, 1.01875104e-01,
7.73459329e-02, 2.50275508e-02, 2.93537540e-02,
1.30949577e-02, -2.15685454e-02],
[2.64330042e-18, 1.45898262e-02, 4.89104186e-02,
7.70703146e-02, 9.55225248e-02, 1.01910945e-01,
7.74050835e-02, 2.52307946e-02, 2.92970736e-02,
1.30880504e-02, -2.15685424e-02],
[2.64318867e-18, 1.45898259e-02, 4.89104184e-02,
7.70703144e-02, 9.55225247e-02, 1.01933432e-01,
7.74421258e-02, 2.53572923e-02, 2.92615130e-02,
1.30837284e-02, -2.15685422e-02],
[2.64305117e-18, 1.45898284e-02, 4.89104206e-02,
7.70703161e-02, 9.55225256e-02, 1.01942593e-01,
7.74571359e-02, 2.54081640e-02, 2.92472117e-02,
1.30819985e-02, -2.15685446e-02],
[2.30141673e-18, 1.40210825e-02, 4.56205547e-02,
6.63109661e-02, 5.79266964e-02, 2.33044622e-15,
4.69672564e-02, 2.18401553e-02, 2.72864925e-02,
1.25728575e-02, -2.10227772e-02],
[1.10672535e-18, 1.04777076e-02, 3.59041065e-02,
4.24614318e-02, 2.24217216e-02, 3.66914762e-15,
1.81728517e-02, 1.39301504e-02, 2.14956836e-02,
1.08711460e-02, -1.90802849e-02]]
)
np.testing.assert_allclose(fd, fd_test, rtol=2e-4)
def parse_json_nshmp(rupts, args):
"""
This will hopefully be the most general json format for rutpures.
Assumes top of ruputure is horizontal and continuous, and that
there is only one segment per rupture (but multiple quads).
Users first and last point to get average strike, which is used
for all quads.
Args:
rupts (dict): Python translation of rupture json file using json.load
method.
args (ArgumentParser): argparse object.
Returns:
dict: Dictionary of rupture information.
"""
rlist = []
nrup = len(rupts['events'])
if args.index is not None:
iter = args.index
iter = map(int, iter)
else:
iter = range(nrup)
for i in iter:
event_name = rupts['events'][i]['desc']
short_name = event_name.split('.xls')[0]
id = rupts['events'][i]['id']
magnitude = rupts['events'][i]['mag']
if 'rake' in rupts['events'][i].keys():
rake = rupts['events'][i]['rake']
else:
rake = np.nan
# Does the file include a rupture model?
if len(rupts['events'][i]['lats']) > 1:
dip = rupts['events'][i]['dip']
width = rupts['events'][i]['width']
ztor = rupts['events'][i]['ztor']
lons = rupts['events'][i]['lons']
lats = rupts['events'][i]['lats']
xp0 = np.array(lons[:-1])
xp1 = np.array(lons[1:])
yp0 = np.array(lats[:-1])
yp1 = np.array(lats[1:])
zp = np.ones_like(xp0) * ztor
dips = np.ones_like(xp0) * dip
widths = np.ones_like(xp0) * width
P1 = geo.point.Point(lons[0], lats[0])
P2 = geo.point.Point(lons[-1], lats[-1])
strike = np.array([P1.azimuth(P2)])
# Dummy origin
origin = Origin({
'mag': 0,
'id': '',
'lat': 0,
'lon': 0,
'depth': 0
})
rupt = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
origin,
strike=strike,
reference=args.reference)
quads = rupt.getQuadrilaterals()
edges = get_rupture_edges(quads) # for hypo placement
hlat, hlon, hdepth = get_hypo(edges, args)
else:
rupt = None
edges = None
hlat = float(rupts['events'][i]['lats'][0])
hlon = float(rupts['events'][i]['lons'][0])
id_str, eventsourcecode, real_desc = get_event_id(event_name,
magnitude,
args.directivity,
args.dirind,
quads,
id=id)
event = {
'lat': hlat,
'lon': hlon,
'depth': hdepth,
'mag': magnitude,
'rake': rake,
'id': id_str,
'locstring': event_name,
'type': 'ALL',
'timezone': 'UTC',
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'created': ShakeDateTime.utcfromtimestamp(int(time.time()))
}
# Update rupture with new origin info
if rupt is not None:
origin = Origin(event)
rupt = QuadRupture.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
origin,
strike=strike,
reference=args.reference)
rdict = {
'rupture': rupt,
'event': event,
'edges': edges,
'id_str': id_str,
'short_name': short_name,
'real_desc': real_desc,
'eventsourcecode': eventsourcecode
}
rlist.append(rdict)
return rlist
def test_so6():
magnitude = 7.2
dip = np.array([70])
rake = 135
width = np.array([15])
L = 80
rupx = np.array([0, 0])
rupy = np.array([0, L])
zp = np.array([0])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
# Dummy origin
origin = Origin({
'lat': 0,
'lon': 0,
'depth': 0,
'mag': 0,
'eventsourcecode': 'so6',
'rake': rake
})
# Rupture
rup = QuadRupture.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
origin,
reference='rv4')
# Sites
x = np.linspace(-80, 80, 21)
y = np.linspace(-50, 130, 21)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
sdepth = np.zeros_like(slon)
# Fix origin
tmp = rup.getQuadrilaterals()[0]
pp0 = Vector.fromPoint(
point.Point(tmp[0].longitude, tmp[0].latitude, tmp[0].depth))
pp1 = Vector.fromPoint(
point.Point(tmp[1].longitude, tmp[1].latitude, tmp[1].depth))
pp2 = Vector.fromPoint(
point.Point(tmp[2].longitude, tmp[2].latitude, tmp[2].depth))
pp3 = Vector.fromPoint(
point.Point(tmp[3].longitude, tmp[3].latitude, tmp[3].depth))
dxp = 10 / L
dyp = (width - 5) / width
mp0 = pp0 + (pp1 - pp0) * dxp
mp1 = pp3 + (pp2 - pp3) * dxp
rp = mp0 + (mp1 - mp0) * dyp
epilat, epilon, epidepth = ecef2latlon(rp.x, rp.y, rp.z)
epix, epiy = proj(epilon, epilat, reverse=False)
origin = Origin({
'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'eventsourcecode': 'so6',
'rake': rake
})
ruplat = [a.latitude for a in rup.getQuadrilaterals()[0]]
ruplon = [a.longitude for a in rup.getQuadrilaterals()[0]]
ruplat = np.append(ruplat, ruplat[0])
ruplon = np.append(ruplon, ruplon[0])
rupx, rupy = proj(ruplon, ruplat, reverse=False)
test1 = Bayless2013(origin, rup, slat, slon, sdepth, T=5)
fd = test1.getFd()
fd_test = np.array([
[
0.00000000e+00, 0.00000000e+00, 0.00000000e+00, -8.92879772e-03,
-1.74526918e-02, -2.22981746e-02, -2.34350450e-02, -2.13620062e-02,
-1.72712346e-02, -1.29509613e-02, -1.02545064e-02, -1.03010185e-02,
-1.28847597e-02, -1.66274727e-02, -1.96984070e-02, -2.05377743e-02,
-1.81831337e-02, -1.21881814e-02, -2.64862879e-03, 0.00000000e+00,
0.00000000e+00
],
[
0.00000000e+00, 0.00000000e+00, -8.73221519e-03, -2.21421374e-02,
-3.18438939e-02, -3.71488270e-02, -3.76239913e-02, -3.35015951e-02,
-2.61748968e-02, -1.83864728e-02, -1.34793002e-02, -1.36687799e-02,
-1.85727143e-02, -2.55527671e-02, -3.14227568e-02, -3.38933995e-02,
-3.19289607e-02, -2.53396980e-02, -1.45943649e-02, -3.71405488e-04,
0.00000000e+00
],
[
0.00000000e+00, -2.54621422e-03, -2.11428566e-02, -3.68609103e-02,
-4.87464747e-02, -5.56539037e-02, -5.64419387e-02, -5.05331157e-02,
-3.52919381e-02, -2.18782050e-02, -1.40858125e-02, -1.47354546e-02,
-2.35727189e-02, -3.74838465e-02, -4.75915414e-02, -5.13000399e-02,
-4.87882409e-02, -4.05716321e-02, -2.77368254e-02, -1.13542729e-02,
0.00000000e+00
],
[
0.00000000e+00, -1.21642958e-02, -3.33747360e-02, -5.21661817e-02,
-6.74724509e-02, -7.77628842e-02, -8.00243748e-02, -6.42496853e-02,
-4.38124530e-02, -1.97027426e-02, -1.45897731e-02, -1.07427056e-02,
-3.08235222e-02, -4.82656988e-02, -6.67692677e-02, -7.35152908e-02,
-6.85574283e-02, -5.71811573e-02, -4.12138780e-02, -2.20396726e-02,
-6.24121310e-04
],
[
0.00000000e+00, -2.00643401e-02, -4.39827328e-02, -6.62722434e-02,
-8.60268414e-02, -1.01730306e-01, -9.86277741e-02, -9.82914922e-02,
-5.22335876e-02, -1.54622435e-02, -1.57487554e-02, -3.06190808e-03,
-4.81481586e-02, -8.92480491e-02, -8.63776477e-02, -9.98130440e-02,
-8.95491230e-02, -7.33553695e-02, -5.34401725e-02, -3.11601812e-02,
-7.33715103e-03
],
[
0.00000000e+00, -2.50053614e-02, -5.11695772e-02, -7.65997026e-02,
-1.00809054e-01, -1.22877573e-01, -1.18738178e-01, -1.55236782e-01,
-7.45388001e-02, 1.92779182e-03, -1.94380016e-02, 1.94922939e-02,
-7.66669920e-02, -1.53909722e-01, -1.10846875e-01, -1.19746768e-01,
-1.07680300e-01, -8.59905101e-02, -6.22042294e-02, -3.71802472e-02,
-1.13867485e-02
],
[
0.00000000e+00, -2.63645827e-02, -5.37984901e-02, -8.11337022e-02,
-1.08298371e-01, -1.35146441e-01, -1.34825430e-01, -1.85836050e-01,
-1.10730875e-01, -3.18861095e-02, 4.14395701e-02, -1.52711946e-02,
-1.31840763e-01, -1.96794707e-01, -1.33453212e-01, -1.34989129e-01,
-1.17922385e-01, -9.21637323e-02, -6.58369237e-02, -3.91646838e-02,
-1.22685698e-02
],
[
0.00000000e+00, -2.64622244e-02, -5.40483999e-02, -8.16190336e-02,
-1.09162854e-01, -1.36656677e-01, -1.37081504e-01, -1.89522811e-01,
-1.17723634e-01, -4.88765748e-02, -5.04529015e-03, -5.76414497e-02,
-1.45712183e-01, -2.03062804e-01, -1.36859828e-01, -1.37107390e-01,
-1.19124650e-01, -9.28263279e-02, -6.61800709e-02, -3.93088682e-02,
-1.22842049e-02
],
[
0.00000000e+00, -2.58466495e-02, -5.24858827e-02, -7.86086164e-02,
-1.03856343e-01, -1.27529509e-01, -1.23794779e-01, -1.68810613e-01,
-8.22602627e-02, 1.74236964e-02, 9.38708725e-02, 4.23208284e-02,
-8.46343723e-02, -1.70476759e-01, -1.17547884e-01, -1.24569752e-01,
-1.11518670e-01, -8.84736806e-02, -6.38037151e-02, -3.81874381e-02,
-1.19867610e-02
],
[
0.00000000e+00, -2.42186547e-02, -4.84175525e-02, -7.09428614e-02,
-9.07754575e-02, -1.06117824e-01, -9.50228292e-02, -1.29781980e-01,
-3.08573454e-02, 7.39058739e-02, 1.30478117e-01, 8.28181149e-02,
-2.70389535e-02, -1.20837502e-01, -8.02081725e-02, -9.70274506e-02,
-9.35853383e-02, -7.77422806e-02, -5.77817530e-02, -3.53067886e-02,
-1.12414659e-02
],
[
0.00000000e+00, -2.16818717e-02, -4.22363856e-02, -5.96909893e-02,
-7.24805224e-02, -7.81867829e-02, -6.11838569e-02, -9.05679744e-02,
9.95934969e-03, 1.07503875e-01, 1.52073917e-01, 1.05894634e-01,
8.68652263e-03, -7.98571818e-02, -4.16548658e-02, -6.40511838e-02,
-6.99337160e-02, -6.26305633e-02, -4.89098800e-02, -3.09284566e-02,
-1.00919381e-02
],
[
0.00000000e+00, -1.84940182e-02, -3.47054606e-02, -4.65278129e-02,
-5.22037664e-02, -4.93977115e-02, -2.95395230e-02, -5.82421092e-02,
3.91025654e-02, 1.29337956e-01, 1.67436703e-01, 1.21969296e-01,
3.20823547e-02, -5.00287386e-02, -9.22993907e-03, -3.27186625e-02,
-4.52706958e-02, -4.57409325e-02, -3.84701291e-02, -2.55751405e-02,
-8.64950254e-03
],
[
0.00000000e+00, -1.49431380e-02, -2.65887341e-02, -3.29162158e-02,
-3.22994323e-02, -2.29081781e-02, -2.60259636e-03, -3.29856530e-02,
6.02631314e-02, 1.45003704e-01, 1.79361264e-01, 1.34292814e-01,
4.88007115e-02, -2.82328554e-02, 1.64212421e-02, -5.72391847e-03,
-2.23438861e-02, -2.90246794e-02, -2.76054402e-02, -1.97779758e-02,
-7.03945406e-03
],
[
0.00000000e+00, -1.12771143e-02, -1.84737590e-02, -1.98228664e-02,
-1.40092305e-02, 1.84580818e-04, 1.95817303e-02, -1.32608487e-02,
7.62783168e-02, 1.57076433e-01, 1.89083905e-01, 1.44259188e-01,
6.15722813e-02, -1.17505212e-02, 3.65938109e-02, 1.66937711e-02,
-2.18970818e-03, -1.35507683e-02, -1.70890527e-02, -1.39519424e-02,
-5.37036892e-03
],
[
0.00000000e+00, -7.67615215e-03, -1.07348257e-02, -7.75276739e-03,
2.22351695e-03, 1.98662250e-02, 3.77611177e-02, 2.42018661e-03,
8.89036172e-02, 1.66855206e-01, 1.97260700e-01, 1.52590263e-01,
7.17981256e-02, 1.18005972e-03, 5.26852303e-02, 3.51638855e-02,
1.51012176e-02, 2.69654076e-04, -7.33815554e-03, -8.36639665e-03,
-3.72176313e-03
],
[
0.00000000e+00, -4.50552324e-03, -4.32262850e-03, 1.73559158e-03,
1.42670366e-02, 3.35040699e-02, 4.97279358e-02, 1.85410528e-02,
9.39950666e-02, 1.46646579e-01, 9.13474746e-02, 1.37004651e-01,
7.74648339e-02, 1.59777072e-02, 6.25334939e-02, 4.74577418e-02,
2.72155518e-02, 1.06174952e-02, 3.94103899e-04, -3.68465400e-03,
-2.19830733e-03
],
[
0.00000000e+00, -1.74629916e-03, 5.44471813e-04, 8.22933499e-03,
2.15699287e-02, 4.04232250e-02, 5.69678048e-02, 5.52408259e-02,
9.04381272e-02, 1.08204635e-01, 9.14439984e-02, 1.06884511e-01,
8.17241884e-02, 5.55282924e-02, 6.78528399e-02, 5.47188925e-02,
3.35251483e-02, 1.69615982e-02, 5.72048628e-03, -8.81437278e-05,
-7.36518436e-04
],
[
0.00000000e+00, 4.07838765e-05, 3.63933766e-03, 1.20080876e-02,
2.51274691e-02, 4.25687176e-02, 6.25685606e-02, 7.33480475e-02,
8.37515545e-02, 9.52500287e-02, 9.15135660e-02, 9.66442834e-02,
8.66659913e-02, 8.10325633e-02, 7.18836713e-02, 5.45548434e-02,
3.55884875e-02, 2.00142359e-02, 8.71200201e-03, 2.04407846e-03,
-6.53680674e-06
],
[
0.00000000e+00, 2.40054729e-04, 4.44975227e-03, 1.27572519e-02,
2.49362989e-02, 4.03831326e-02, 5.80039988e-02, 7.61280192e-02,
8.37404162e-02, 8.89634569e-02, 9.15651607e-02, 9.13586235e-02,
8.83589144e-02, 8.27804032e-02, 6.75666471e-02, 5.00483249e-02,
3.36733366e-02, 1.96758691e-02, 9.00603204e-03, 2.18370401e-03,
0.00000000e+00
],
[
0.00000000e+00, 0.00000000e+00, 2.78776980e-03, 1.05086036e-02,
2.13238822e-02, 3.45577738e-02, 4.91570145e-02, 6.36787133e-02,
7.63710088e-02, 8.54072310e-02, 8.92960200e-02, 8.75702197e-02,
8.07095447e-02, 6.97999389e-02, 5.63787286e-02, 4.20734776e-02,
2.83073312e-02, 1.61614525e-02, 6.56194125e-03, 1.00721924e-04,
0.00000000e+00
],
[
0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 5.49667845e-03,
1.47563319e-02, 2.57955743e-02, 3.76689418e-02, 4.91861917e-02,
5.90108907e-02, 6.58478416e-02, 6.87018515e-02, 6.73174642e-02,
6.20270643e-02, 5.35456385e-02, 4.29400416e-02, 3.14129728e-02,
2.00795162e-02, 9.84001885e-03, 1.53992995e-03, 0.00000000e+00,
0.00000000e+00
]
])
np.testing.assert_allclose(fd, fd_test, rtol=1e-4)
def test_ss3_move_hypo1():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0.0])
epix = np.array([1.0])
epiy = np.array([-1.0])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin
origin = Origin({
'lat': epilat[0],
'lon': epilon[0],
'depth': -1,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake
})
rup = QuadRupture.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
origin,
reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
phyp = copy.deepcopy(test1.phyp[0])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.004233219183604, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989205968, rtol=1e-4)
# --------------------------------------------------------------------------
# Also for multiple segments
# --------------------------------------------------------------------------
dip = np.array([90., 90., 90.])
rake = 180.0
width = np.array([15., 15., 10.])
rupx = np.array([0., 0., 10., 20.])
rupy = np.array([0., 20., 60., 80.])
zp = np.array([0., 0., 0.])
epix = np.array([0.])
epiy = np.array([0.])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
rup = QuadRupture.fromTrace(np.array(tlon[0:3]),
np.array(tlat[0:3]),
np.array(tlon[1:4]),
np.array(tlat[1:4]),
zp,
width,
dip,
origin,
reference='')
event = {
'lat': epilat[0],
'lon': epilon[0],
'depth': 1.0,
'mag': magnitude,
'eventsourcecode': '',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'
}
event['time'] = HistoricTime.utcfromtimestamp(int(time.time()))
event['created'] = HistoricTime.utcfromtimestamp(int(time.time()))
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
origin = Origin(event)
origin.rake = rake
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# 1st pseudo-hyp
phyp = copy.deepcopy(test1.phyp[0])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.004233219183604, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989205968, rtol=1e-4)
# 2nd pseudo-hyp
phyp = copy.deepcopy(test1.phyp[1])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.184097835787796, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989103525, rtol=1e-4)
# 3rd pseudo-hyp
phyp = copy.deepcopy(test1.phyp[2])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.543778594535752, rtol=1e-4)
np.testing.assert_allclose(plon, -120.87137783362499, rtol=1e-4)
np.testing.assert_allclose(pdep, 4.9999999995063993, rtol=1e-4)
def test_ss3():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin:
origin = Origin({
'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake
})
rup = QuadRupture.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
origin,
reference='ss3')
x = np.linspace(-60, 60, 21)
y = np.linspace(-60, 138, 34)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array([
[
0.00000000e+00, 0.00000000e+00, 2.14620746e-03, 6.47899336e-03,
1.23119791e-02, 1.91676140e-02, 2.64009788e-02, 3.32427846e-02,
3.88863288e-02, 4.26104002e-02, 4.39120296e-02, 4.26104002e-02,
3.88863288e-02, 3.32427846e-02, 2.64009788e-02, 1.91676140e-02,
1.23119791e-02, 6.47899336e-03, 2.14620746e-03, 0.00000000e+00,
0.00000000e+00
],
[
0.00000000e+00, 8.57780996e-04, 3.99405791e-03, 9.31948105e-03,
1.65406113e-02, 2.51316805e-02, 3.43205435e-02, 4.31274592e-02,
5.04747209e-02, 5.53634169e-02, 5.70796092e-02, 5.53634169e-02,
5.04747209e-02, 4.31274592e-02, 3.43205435e-02, 2.51316805e-02,
1.65406113e-02, 9.31948105e-03, 3.99405791e-03, 8.57780996e-04,
0.00000000e+00
],
[
-7.32594549e-04, 1.80425497e-04, 3.76908220e-03, 1.00175179e-02,
1.86854835e-02, 2.92291145e-02, 4.07487277e-02, 5.20057177e-02,
6.15509770e-02, 6.79776087e-02, 7.02477931e-02, 6.79776087e-02,
6.15509770e-02, 5.20057177e-02, 4.07487277e-02, 2.92291145e-02,
1.86854835e-02, 1.00175179e-02, 3.76908220e-03, 1.80425497e-04,
-7.32594549e-04
],
[
-3.29238561e-03, -2.60643191e-03, 1.16635260e-03, 8.15185259e-03,
1.82290773e-02, 3.08983182e-02, 4.51608038e-02, 5.94769126e-02,
7.18919113e-02, 8.03888307e-02, 8.34165399e-02, 8.03888307e-02,
7.18919113e-02, 5.94769126e-02, 4.51608038e-02, 3.08983182e-02,
1.82290773e-02, 8.15185259e-03, 1.16635260e-03, -2.60643191e-03,
-3.29238561e-03
],
[
-7.68543266e-03, -7.63179286e-03, -4.08866637e-03, 3.27605236e-03,
1.45558215e-02, 2.94068040e-02, 4.68176355e-02, 6.49397159e-02,
7.72066272e-02, 8.50445368e-02, 8.77974692e-02, 8.50445368e-02,
7.72066272e-02, 6.49397159e-02, 4.68176355e-02, 2.94068040e-02,
1.45558215e-02, 3.27605236e-03, -4.08866637e-03, -7.63179286e-03,
-7.68543266e-03
],
[
-1.38078234e-02, -1.49011067e-02, -1.21731364e-02, -5.02168047e-03,
6.98177526e-03, 2.38268531e-02, 4.30419205e-02, 6.00041964e-02,
7.44541603e-02, 8.42939552e-02, 8.77989590e-02, 8.42939552e-02,
7.44541603e-02, 6.00041964e-02, 4.30419205e-02, 2.38268531e-02,
6.98177526e-03, -5.02168047e-03, -1.21731364e-02, -1.49011067e-02,
-1.38078234e-02
],
[
-2.13780396e-02, -2.42165379e-02, -2.30613142e-02, -1.70011475e-02,
-5.15036128e-03, 1.25885635e-02, 3.24536739e-02, 5.25619351e-02,
7.05100243e-02, 8.31900906e-02, 8.78003567e-02, 8.31900906e-02,
7.05100243e-02, 5.25619351e-02, 3.24536739e-02, 1.25885635e-02,
-5.15036128e-03, -1.70011475e-02, -2.30613142e-02, -2.42165379e-02,
-2.13780396e-02
],
[
-2.98882710e-02, -3.50862342e-02, -3.63793490e-02, -3.25716319e-02,
-2.22546618e-02, -3.59274163e-03, 1.83064517e-02, 4.20112440e-02,
6.46115966e-02, 8.14746164e-02, 8.78016623e-02, 8.14746164e-02,
6.46115966e-02, 4.20112440e-02, 1.83064517e-02, -3.59274163e-03,
-2.22546618e-02, -3.25716319e-02, -3.63793490e-02, -3.50862342e-02,
-2.98882710e-02
],
[
-3.85810679e-02, -4.66488633e-02, -5.12430987e-02, -5.10089462e-02,
-4.20856023e-02, -2.36905234e-02, -6.33876287e-04, 2.66765430e-02,
5.53289928e-02, 7.86066125e-02, 8.78028757e-02, 7.86066125e-02,
5.53289928e-02, 2.66765430e-02, -6.33876287e-04, -2.36905234e-02,
-4.20856023e-02, -5.10089462e-02, -5.12430987e-02, -4.66488633e-02,
-3.85810679e-02
],
[
-4.64803335e-02, -5.76615888e-02, -6.61458422e-02, -7.06512643e-02,
-6.38427394e-02, -4.77258398e-02, -2.55483969e-02, 4.05840724e-03,
3.98470070e-02, 7.33053399e-02, 8.78039969e-02, 7.33053399e-02,
3.98470070e-02, 4.05840724e-03, -2.55483969e-02, -4.77258398e-02,
-6.38427394e-02, -7.06512643e-02, -6.61458422e-02, -5.76615888e-02,
-4.64803335e-02
],
[
-5.25038299e-02, -6.66129442e-02, -7.90147081e-02, -8.87629178e-02,
-8.59653118e-02, -7.42828398e-02, -5.64316505e-02, -2.87083225e-02,
1.25945312e-02, 6.19971667e-02, 8.78050260e-02, 6.19971667e-02,
1.25945312e-02, -2.87083225e-02, -5.64316505e-02, -7.42828398e-02,
-8.59653118e-02, -8.87629178e-02, -7.90147081e-02, -6.66129442e-02,
-5.25038299e-02
],
[
-5.69779111e-02, -7.36791817e-02, -8.97495345e-02, -1.04799583e-01,
-1.07737239e-01, -1.02875880e-01, -9.46568471e-02, -7.95630162e-02,
-4.96285112e-02, 6.59954795e-03, 5.25569882e-02, 6.59954795e-03,
-4.96285112e-02, -7.95630162e-02, -9.46568471e-02, -1.02875880e-01,
-1.07737239e-01, -1.04799583e-01, -8.97495345e-02, -7.36791817e-02,
-5.69779111e-02
],
[
-5.90357675e-02, -7.69727119e-02, -9.48442826e-02, -1.12607620e-01,
-1.18744885e-01, -1.18201834e-01, -1.17217017e-01, -1.15152899e-01,
-1.09694433e-01, -8.82341332e-02, -1.61624035e-02, -8.82341332e-02,
-1.09694433e-01, -1.15152899e-01, -1.17217017e-01, -1.18201834e-01,
-1.18744885e-01, -1.12607620e-01, -9.48442826e-02, -7.69727119e-02,
-5.90357675e-02
],
[
-5.92189452e-02, -7.72680305e-02, -9.53051857e-02, -1.13322519e-01,
-1.19770917e-01, -1.19670660e-01, -1.19486798e-01, -1.19092639e-01,
-1.17989113e-01, -1.12555820e-01, -4.50009776e-02, -1.12555820e-01,
-1.17989113e-01, -1.19092639e-01, -1.19486798e-01, -1.19670660e-01,
-1.19770917e-01, -1.13322519e-01, -9.53051857e-02, -7.72680305e-02,
-5.92189452e-02
],
[
-5.79249958e-02, -7.51927112e-02, -9.20842554e-02, -1.08361430e-01,
-1.12722790e-01, -1.09732675e-01, -1.04531672e-01, -9.44729544e-02,
-7.23277773e-02, -2.05699911e-02, 3.58249631e-02, -2.05699911e-02,
-7.23277773e-02, -9.44729544e-02, -1.04531672e-01, -1.09732675e-01,
-1.12722790e-01, -1.08361430e-01, -9.20842554e-02, -7.51927112e-02,
-5.79249958e-02
],
[
-5.42527703e-02, -6.93641123e-02, -8.31684773e-02, -9.49114165e-02,
-9.41989454e-02, -8.48645354e-02, -7.00894708e-02, -4.58286259e-02,
-6.37563061e-03, 4.68887998e-02, 7.77968419e-02, 4.68887998e-02,
-6.37563061e-03, -4.58286259e-02, -7.00894708e-02, -8.48645354e-02,
-9.41989454e-02, -9.49114165e-02, -8.31684773e-02, -6.93641123e-02,
-5.42527703e-02
],
[
-4.82490057e-02, -5.99997941e-02, -6.91786120e-02, -7.44891242e-02,
-6.73705808e-02, -5.13001284e-02, -2.84188057e-02, 3.60143816e-03,
4.47470123e-02, 8.58663851e-02, 1.04548354e-01, 8.58663851e-02,
4.47470123e-02, 3.60143816e-03, -2.84188057e-02, -5.13001284e-02,
-6.73705808e-02, -7.44891242e-02, -6.91786120e-02, -5.99997941e-02,
-4.82490057e-02
],
[
-4.03203010e-02, -4.79063206e-02, -5.16352259e-02, -4.98707253e-02,
-3.67295509e-02, -1.57342058e-02, 1.13668830e-02, 4.46551184e-02,
8.10450840e-02, 1.11780747e-01, 1.24226598e-01, 1.11780747e-01,
8.10450840e-02, 4.46551184e-02, 1.13668830e-02, -1.57342058e-02,
-3.67295509e-02, -4.98707253e-02, -5.16352259e-02, -4.79063206e-02,
-4.03203010e-02
],
[
-3.10250239e-02, -3.40796094e-02, -3.22089254e-02, -2.37094100e-02,
-5.85463114e-03, 1.77402761e-02, 4.57786845e-02, 7.69637052e-02,
1.07537652e-01, 1.30906328e-01, 1.39800436e-01, 1.30906328e-01,
1.07537652e-01, 7.69637052e-02, 4.57786845e-02, 1.77402761e-02,
-5.85463114e-03, -2.37094100e-02, -3.22089254e-02, -3.40796094e-02,
-3.10250239e-02
],
[
-2.09301700e-02, -1.94475962e-02, -1.22970199e-02, 2.07296407e-03,
2.31516868e-02, 4.74574033e-02, 7.44743481e-02, 1.02380049e-01,
1.27776301e-01, 1.46003379e-01, 1.52690015e-01, 1.46003379e-01,
1.27776301e-01, 1.02380049e-01, 7.44743481e-02, 4.74574033e-02,
2.31516868e-02, 2.07296407e-03, -1.22970199e-02, -1.94475962e-02,
-2.09301700e-02
],
[
-1.05257992e-02, -4.74329696e-03, 7.12107274e-03, 2.63431361e-02,
4.93709790e-02, 7.31527220e-02, 9.82233938e-02, 1.22728059e-01,
1.43894925e-01, 1.58465026e-01, 1.63685984e-01, 1.58465026e-01,
1.43894925e-01, 1.22728059e-01, 9.82233938e-02, 7.31527220e-02,
4.93709790e-02, 2.63431361e-02, 7.12107274e-03, -4.74329696e-03,
-1.05257992e-02
],
[
-1.89098657e-04, 9.52392382e-03, 2.54577716e-02, 4.85730869e-02,
7.26048516e-02, 9.51726659e-02, 1.17988523e-01, 1.39380421e-01,
1.57176612e-01, 1.69076915e-01, 1.73274075e-01, 1.69076915e-01,
1.57176612e-01, 1.39380421e-01, 1.17988523e-01, 9.51726659e-02,
7.26048516e-02, 4.85730869e-02, 2.54577716e-02, 9.52392382e-03,
-1.89098657e-04
],
[
9.81732797e-03, 2.30419581e-02, 4.24234701e-02, 6.86213308e-02,
9.30164618e-02, 1.14050063e-01, 1.34620894e-01, 1.53304069e-01,
1.68420867e-01, 1.78321253e-01, 1.81774183e-01, 1.78321253e-01,
1.68420867e-01, 1.53304069e-01, 1.34620894e-01, 1.14050063e-01,
9.30164618e-02, 6.86213308e-02, 4.24234701e-02, 2.30419581e-02,
9.81732797e-03
],
[
1.93290725e-02, 3.56493099e-02, 5.79271157e-02, 8.65611122e-02,
1.10914315e-01, 1.30317702e-01, 1.48798006e-01, 1.65173224e-01,
1.78147031e-01, 1.86513895e-01, 1.89408199e-01, 1.86513895e-01,
1.78147031e-01, 1.65173224e-01, 1.48798006e-01, 1.30317702e-01,
1.10914315e-01, 8.65611122e-02, 5.79271157e-02, 3.56493099e-02,
1.93290725e-02
],
[
2.68168937e-02, 4.52356810e-02, 6.92261217e-02, 9.89630241e-02,
1.23093435e-01, 1.40640067e-01, 1.56998943e-01, 1.71215219e-01,
1.82297185e-01, 1.89360704e-01, 1.91789146e-01, 1.89360704e-01,
1.82297185e-01, 1.71215219e-01, 1.56998943e-01, 1.40640067e-01,
1.23093435e-01, 9.89630241e-02, 6.92261217e-02, 4.52356810e-02,
2.68168937e-02
],
[
3.19403269e-02, 5.15051953e-02, 7.61032066e-02, 1.05705197e-01,
1.31722206e-01, 1.47466588e-01, 1.61892450e-01, 1.74235616e-01,
1.83735386e-01, 1.89735533e-01, 1.91788616e-01, 1.89735533e-01,
1.83735386e-01, 1.74235616e-01, 1.61892450e-01, 1.47466588e-01,
1.31722206e-01, 1.05705197e-01, 7.61032066e-02, 5.15051953e-02,
3.19403269e-02
],
[
3.48604070e-02, 5.49292382e-02, 7.94274234e-02, 1.08149011e-01,
1.38923419e-01, 1.53070440e-01, 1.65849067e-01, 1.76646162e-01,
1.84871647e-01, 1.90029617e-01, 1.91787948e-01, 1.90029617e-01,
1.84871647e-01, 1.76646162e-01, 1.65849067e-01, 1.53070440e-01,
1.38923419e-01, 1.08149011e-01, 7.94274234e-02, 5.49292382e-02,
3.48604070e-02
],
[
3.53402022e-02, 5.53653759e-02, 7.91965502e-02, 1.06486934e-01,
1.36563003e-01, 1.57713955e-01, 1.69087164e-01, 1.78598269e-01,
1.85784340e-01, 1.90264452e-01, 1.91787141e-01, 1.90264452e-01,
1.85784340e-01, 1.78598269e-01, 1.69087164e-01, 1.57713955e-01,
1.36563003e-01, 1.06486934e-01, 7.91965502e-02, 5.53653759e-02,
3.53402022e-02
],
[
3.32889822e-02, 5.28319225e-02, 7.55769079e-02, 1.01077605e-01,
1.28592068e-01, 1.57023616e-01, 1.71766715e-01, 1.80199729e-01,
1.86528091e-01, 1.90454829e-01, 1.91786196e-01, 1.90454829e-01,
1.86528091e-01, 1.80199729e-01, 1.71766715e-01, 1.57023616e-01,
1.28592068e-01, 1.01077605e-01, 7.55769079e-02, 5.28319225e-02,
3.32889822e-02
],
[
2.87295370e-02, 4.74613283e-02, 6.88388861e-02, 9.23568989e-02,
1.17254645e-01, 1.42483223e-01, 1.66695764e-01, 1.81528776e-01,
1.87141877e-01, 1.90611190e-01, 1.91785112e-01, 1.90611190e-01,
1.87141877e-01, 1.81528776e-01, 1.66695764e-01, 1.42483223e-01,
1.17254645e-01, 9.23568989e-02, 6.88388861e-02, 4.74613283e-02,
2.87295370e-02
],
[
2.17650266e-02, 3.94568191e-02, 5.93023344e-02, 8.07720575e-02,
1.03124482e-01, 1.25394282e-01, 1.46405870e-01, 1.64828303e-01,
1.79288925e-01, 1.88553222e-01, 1.91747252e-01, 1.88553222e-01,
1.79288925e-01, 1.64828303e-01, 1.46405870e-01, 1.25394282e-01,
1.03124482e-01, 8.07720575e-02, 5.93023344e-02, 3.94568191e-02,
2.17650266e-02
],
[
1.25495284e-02, 2.90572166e-02, 4.72972116e-02, 6.67423656e-02,
8.66951873e-02, 1.06290296e-01, 1.24520131e-01, 1.40293247e-01,
1.52531693e-01, 1.60303860e-01, 1.62970689e-01, 1.60303860e-01,
1.52531693e-01, 1.40293247e-01, 1.24520131e-01, 1.06290296e-01,
8.66951873e-02, 6.67423656e-02, 4.72972116e-02, 2.90572166e-02,
1.25495284e-02
],
[
1.26441934e-03, 1.65114811e-02, 3.31390978e-02, 5.06407706e-02,
6.83765492e-02, 8.55839448e-02, 1.01408074e-01, 1.14955639e-01,
1.25373662e-01, 1.31946425e-01, 1.34193829e-01, 1.31946425e-01,
1.25373662e-01, 1.14955639e-01, 1.01408074e-01, 8.55839448e-02,
6.83765492e-02, 5.06407706e-02, 3.31390978e-02, 1.65114811e-02,
1.26441934e-03
],
[
0.00000000e+00, 2.06213867e-03, 1.71162845e-02, 3.27888240e-02,
4.85026462e-02, 6.35932476e-02, 7.73387997e-02, 8.90069217e-02,
9.79166934e-02, 1.03509489e-01, 1.05416736e-01, 1.03509489e-01,
9.79166934e-02, 8.90069217e-02, 7.73387997e-02, 6.35932476e-02,
4.85026462e-02, 3.27888240e-02, 1.71162845e-02, 2.06213867e-03,
0.00000000e+00
]
])
np.testing.assert_allclose(fd, fd_test, rtol=1e-4)
def test_EdgeRupture():
# Rupture requires an origin even when not used:
origin = Origin({'eventsourcecode': 'test', 'lat': 0, 'lon': 0,
'depth': 5.0, 'mag': 7.0})
file = os.path.join(homedir, 'rupture_data/cascadia.json')
rup = get_rupture(origin, file)
np.testing.assert_allclose(rup.getArea(), 105635.92827547337)
# Force read Northridge as EdgeRupture
file = os.path.join(homedir, 'rupture_data/northridge_fault.txt')
d = text_to_json(file)
rupt = EdgeRupture(d, origin)
strike = rupt.getStrike()
np.testing.assert_allclose(strike, 121.97, atol=0.01)
dip = rupt.getDip()
np.testing.assert_allclose(dip, 40.12, atol=0.01)
L = rupt.getLength()
np.testing.assert_allclose(L, 17.99, atol=0.01)
W = rupt.getWidth()
np.testing.assert_allclose(W, 23.92, atol=0.01)
ztor = rupt.getDepthToTop()
np.testing.assert_allclose(ztor, 5, atol=0.01)
# And again for the same vertices but reversed order
file = os.path.join(homedir, 'rupture_data/northridge_fixed_fault.txt')
d = text_to_json(file)
rupt = EdgeRupture(d, origin)
strike = rupt.getStrike()
np.testing.assert_allclose(strike, 121.97, atol=0.01)
dip = rupt.getDip()
np.testing.assert_allclose(dip, 40.12, atol=0.01)
L = rupt.getLength()
np.testing.assert_allclose(L, 17.99, atol=0.01)
W = rupt.getWidth()
np.testing.assert_allclose(W, 23.92, atol=0.01)
ztor = rupt.getDepthToTop()
np.testing.assert_allclose(ztor, 5, atol=0.01)
# Test for fromArrays method
toplats = np.array([37.0, 38.0])
toplons = np.array([-120.0, -120.0])
topdeps = np.array([0.0, 0.0])
botlats = copy.copy(toplats)
botlons = copy.copy(toplons)
botdeps = np.array([10.0, 10.0])
erup = EdgeRupture.fromArrays(toplons, toplats, topdeps, botlons, botlats,
botdeps, origin)
qrup = QuadRupture.fromVertices(
[toplons[0]], [toplats[0]], [topdeps[0]],
[toplons[1]], [toplats[1]], [topdeps[1]],
[botlons[1]], [botlats[1]], [botdeps[1]],
[botlons[0]], [botlats[0]], [botdeps[0]],
origin)
np.testing.assert_allclose(erup.getArea(), 1108.9414759967776)
np.testing.assert_allclose(erup.getDepthToTop(), 0)
np.testing.assert_allclose(erup.getLength(), 111.19492664455889)
np.testing.assert_allclose(
erup.lats, np.array([37., 38., 38., 37., 37., np.nan]))
np.testing.assert_allclose(
erup.lons, np.array([-120., -120., -120., -120., -120., np.nan]))
np.testing.assert_allclose(
erup.depths, np.array([0., 0., 10., 10., 0., np.nan]))
np.testing.assert_allclose(
erup._getGroupIndex(), np.array([0., 0.]))
quads = erup.getQuadrilaterals()
np.testing.assert_allclose(quads[0][0].x, -120.0)
# Need to also test the distances with EdgeRupture
lons = np.linspace(-120.1, -121.0, 10)
lats = np.linspace(37.0, 38, 10)
deps = np.zeros_like(lons)
rrup1 = qrup.computeRrup(lons, lats, deps)
rrup2 = erup.computeRrup(lons, lats, deps)
np.testing.assert_allclose(rrup1, rrup2, atol=2e-2)
rjb1 = qrup.computeRjb(lons, lats, deps)
rjb2 = erup.computeRjb(lons, lats, deps)
np.testing.assert_allclose(rjb1, rjb2, atol=2e-2)
gc2 = erup.computeGC2(lons, lats, deps)
targetRy0 = np.array(
[0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.67335931])
targetRx = np.array(
[-8.88024949, -17.73390996, -26.56167797, -35.3634266,
-44.13902929, -52.88835984, -61.61129242, -70.30770154,
-78.97746209, -87.6204493])
np.testing.assert_allclose(gc2['ry0'], targetRy0)
np.testing.assert_allclose(gc2['rx'], targetRx)
def test_so6():
magnitude = 7.2
dip = np.array([70])
rake = 135
width = np.array([15])
L = 80
rupx = np.array([0, 0])
rupy = np.array([0, L])
zp = np.array([0])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
# Dummy origin
origin = Origin({'lat': 0,
'lon': 0,
'depth': 0,
'mag': 0,
'eventsourcecode': 'so6',
'rake': rake})
# Rupture
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='rv4')
# Sites
x = np.linspace(-80, 80, 21)
y = np.linspace(-50, 130, 21)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
sdepth = np.zeros_like(slon)
# Fix origin
tmp = rup.getQuadrilaterals()[0]
pp0 = Vector.fromPoint(point.Point(
tmp[0].longitude, tmp[0].latitude, tmp[0].depth))
pp1 = Vector.fromPoint(point.Point(
tmp[1].longitude, tmp[1].latitude, tmp[1].depth))
pp2 = Vector.fromPoint(point.Point(
tmp[2].longitude, tmp[2].latitude, tmp[2].depth))
pp3 = Vector.fromPoint(point.Point(
tmp[3].longitude, tmp[3].latitude, tmp[3].depth))
dxp = 10 / L
dyp = (width - 5) / width
mp0 = pp0 + (pp1 - pp0) * dxp
mp1 = pp3 + (pp2 - pp3) * dxp
rp = mp0 + (mp1 - mp0) * dyp
epilat, epilon, epidepth = ecef2latlon(rp.x, rp.y, rp.z)
epix, epiy = proj(epilon, epilat, reverse=False)
origin = Origin({'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'eventsourcecode': 'so6',
'rake': rake})
ruplat = [a.latitude for a in rup.getQuadrilaterals()[0]]
ruplon = [a.longitude for a in rup.getQuadrilaterals()[0]]
ruplat = np.append(ruplat, ruplat[0])
ruplon = np.append(ruplon, ruplon[0])
rupx, rupy = proj(ruplon, ruplat, reverse=False)
test1 = Bayless2013(origin, rup, slat, slon, sdepth, T=5)
fd = test1.getFd()
fd_test = np.array(
[[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
-8.92879772e-03, -1.74526918e-02, -2.22981746e-02,
-2.34350450e-02, -2.13620062e-02, -1.72712346e-02,
-1.29509613e-02, -1.02545064e-02, -1.03010185e-02,
-1.28847597e-02, -1.66274727e-02, -1.96984070e-02,
-2.05377743e-02, -1.81831337e-02, -1.21881814e-02,
-2.64862879e-03, 0.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, -8.73221519e-03,
-2.21421374e-02, -3.18438939e-02, -3.71488270e-02,
-3.76239913e-02, -3.35015951e-02, -2.61748968e-02,
-1.83864728e-02, -1.34793002e-02, -1.36687799e-02,
-1.85727143e-02, -2.55527671e-02, -3.14227568e-02,
-3.38933995e-02, -3.19289607e-02, -2.53396980e-02,
-1.45943649e-02, -3.71405488e-04, 0.00000000e+00],
[0.00000000e+00, -2.54621422e-03, -2.11428566e-02,
-3.68609103e-02, -4.87464747e-02, -5.56539037e-02,
-5.64419387e-02, -5.05331157e-02, -3.52919381e-02,
-2.18782050e-02, -1.40858125e-02, -1.47354546e-02,
-2.35727189e-02, -3.74838465e-02, -4.75915414e-02,
-5.13000399e-02, -4.87882409e-02, -4.05716321e-02,
-2.77368254e-02, -1.13542729e-02, 0.00000000e+00],
[0.00000000e+00, -1.21642958e-02, -3.33747360e-02,
-5.21661817e-02, -6.74724509e-02, -7.77628842e-02,
-8.00243748e-02, -6.42496853e-02, -4.38124530e-02,
-1.97027426e-02, -1.45897731e-02, -1.07427056e-02,
-3.08235222e-02, -4.82656988e-02, -6.67692677e-02,
-7.35152908e-02, -6.85574283e-02, -5.71811573e-02,
-4.12138780e-02, -2.20396726e-02, -6.24121310e-04],
[0.00000000e+00, -2.00643401e-02, -4.39827328e-02,
-6.62722434e-02, -8.60268414e-02, -1.01730306e-01,
-9.86277741e-02, -9.82914922e-02, -5.22335876e-02,
-1.54622435e-02, -1.57487554e-02, -3.06190808e-03,
-4.81481586e-02, -8.92480491e-02, -8.63776477e-02,
-9.98130440e-02, -8.95491230e-02, -7.33553695e-02,
-5.34401725e-02, -3.11601812e-02, -7.33715103e-03],
[0.00000000e+00, -2.50053614e-02, -5.11695772e-02,
-7.65997026e-02, -1.00809054e-01, -1.22877573e-01,
-1.18738178e-01, -1.55236782e-01, -7.45388001e-02,
1.92779182e-03, -1.94380016e-02, 1.94922939e-02,
-7.66669920e-02, -1.53909722e-01, -1.10846875e-01,
-1.19746768e-01, -1.07680300e-01, -8.59905101e-02,
-6.22042294e-02, -3.71802472e-02, -1.13867485e-02],
[0.00000000e+00, -2.63645827e-02, -5.37984901e-02,
-8.11337022e-02, -1.08298371e-01, -1.35146441e-01,
-1.34825430e-01, -1.85836050e-01, -1.10730875e-01,
-3.18861095e-02, 4.14395701e-02, -1.52711946e-02,
-1.31840763e-01, -1.96794707e-01, -1.33453212e-01,
-1.34989129e-01, -1.17922385e-01, -9.21637323e-02,
-6.58369237e-02, -3.91646838e-02, -1.22685698e-02],
[0.00000000e+00, -2.64622244e-02, -5.40483999e-02,
-8.16190336e-02, -1.09162854e-01, -1.36656677e-01,
-1.37081504e-01, -1.89522811e-01, -1.17723634e-01,
-4.88765748e-02, -5.04529015e-03, -5.76414497e-02,
-1.45712183e-01, -2.03062804e-01, -1.36859828e-01,
-1.37107390e-01, -1.19124650e-01, -9.28263279e-02,
-6.61800709e-02, -3.93088682e-02, -1.22842049e-02],
[0.00000000e+00, -2.58466495e-02, -5.24858827e-02,
-7.86086164e-02, -1.03856343e-01, -1.27529509e-01,
-1.23794779e-01, -1.68810613e-01, -8.22602627e-02,
1.74236964e-02, 9.38708725e-02, 4.23208284e-02,
-8.46343723e-02, -1.70476759e-01, -1.17547884e-01,
-1.24569752e-01, -1.11518670e-01, -8.84736806e-02,
-6.38037151e-02, -3.81874381e-02, -1.19867610e-02],
[0.00000000e+00, -2.42186547e-02, -4.84175525e-02,
-7.09428614e-02, -9.07754575e-02, -1.06117824e-01,
-9.50228292e-02, -1.29781980e-01, -3.08573454e-02,
7.39058739e-02, 1.30478117e-01, 8.28181149e-02,
-2.70389535e-02, -1.20837502e-01, -8.02081725e-02,
-9.70274506e-02, -9.35853383e-02, -7.77422806e-02,
-5.77817530e-02, -3.53067886e-02, -1.12414659e-02],
[0.00000000e+00, -2.16818717e-02, -4.22363856e-02,
-5.96909893e-02, -7.24805224e-02, -7.81867829e-02,
-6.11838569e-02, -9.05679744e-02, 9.95934969e-03,
1.07503875e-01, 1.52073917e-01, 1.05894634e-01,
8.68652263e-03, -7.98571818e-02, -4.16548658e-02,
-6.40511838e-02, -6.99337160e-02, -6.26305633e-02,
-4.89098800e-02, -3.09284566e-02, -1.00919381e-02],
[0.00000000e+00, -1.84940182e-02, -3.47054606e-02,
-4.65278129e-02, -5.22037664e-02, -4.93977115e-02,
-2.95395230e-02, -5.82421092e-02, 3.91025654e-02,
1.29337956e-01, 1.67436703e-01, 1.21969296e-01,
3.20823547e-02, -5.00287386e-02, -9.22993907e-03,
-3.27186625e-02, -4.52706958e-02, -4.57409325e-02,
-3.84701291e-02, -2.55751405e-02, -8.64950254e-03],
[0.00000000e+00, -1.49431380e-02, -2.65887341e-02,
-3.29162158e-02, -3.22994323e-02, -2.29081781e-02,
-2.60259636e-03, -3.29856530e-02, 6.02631314e-02,
1.45003704e-01, 1.79361264e-01, 1.34292814e-01,
4.88007115e-02, -2.82328554e-02, 1.64212421e-02,
-5.72391847e-03, -2.23438861e-02, -2.90246794e-02,
-2.76054402e-02, -1.97779758e-02, -7.03945406e-03],
[0.00000000e+00, -1.12771143e-02, -1.84737590e-02,
-1.98228664e-02, -1.40092305e-02, 1.84580818e-04,
1.95817303e-02, -1.32608487e-02, 7.62783168e-02,
1.57076433e-01, 1.89083905e-01, 1.44259188e-01,
6.15722813e-02, -1.17505212e-02, 3.65938109e-02,
1.66937711e-02, -2.18970818e-03, -1.35507683e-02,
-1.70890527e-02, -1.39519424e-02, -5.37036892e-03],
[0.00000000e+00, -7.67615215e-03, -1.07348257e-02,
-7.75276739e-03, 2.22351695e-03, 1.98662250e-02,
3.77611177e-02, 2.42018661e-03, 8.89036172e-02,
1.66855206e-01, 1.97260700e-01, 1.52590263e-01,
7.17981256e-02, 1.18005972e-03, 5.26852303e-02,
3.51638855e-02, 1.51012176e-02, 2.69654076e-04,
-7.33815554e-03, -8.36639665e-03, -3.72176313e-03],
[0.00000000e+00, -4.50552324e-03, -4.32262850e-03,
1.73559158e-03, 1.42670366e-02, 3.35040699e-02,
4.97279358e-02, 1.85410528e-02, 9.39950666e-02,
1.46646579e-01, 9.13474746e-02, 1.37004651e-01,
7.74648339e-02, 1.59777072e-02, 6.25334939e-02,
4.74577418e-02, 2.72155518e-02, 1.06174952e-02,
3.94103899e-04, -3.68465400e-03, -2.19830733e-03],
[0.00000000e+00, -1.74629916e-03, 5.44471813e-04,
8.22933499e-03, 2.15699287e-02, 4.04232250e-02,
5.69678048e-02, 5.52408259e-02, 9.04381272e-02,
1.08204635e-01, 9.14439984e-02, 1.06884511e-01,
8.17241884e-02, 5.55282924e-02, 6.78528399e-02,
5.47188925e-02, 3.35251483e-02, 1.69615982e-02,
5.72048628e-03, -8.81437278e-05, -7.36518436e-04],
[0.00000000e+00, 4.07838765e-05, 3.63933766e-03,
1.20080876e-02, 2.51274691e-02, 4.25687176e-02,
6.25685606e-02, 7.33480475e-02, 8.37515545e-02,
9.52500287e-02, 9.15135660e-02, 9.66442834e-02,
8.66659913e-02, 8.10325633e-02, 7.18836713e-02,
5.45548434e-02, 3.55884875e-02, 2.00142359e-02,
8.71200201e-03, 2.04407846e-03, -6.53680674e-06],
[0.00000000e+00, 2.40054729e-04, 4.44975227e-03,
1.27572519e-02, 2.49362989e-02, 4.03831326e-02,
5.80039988e-02, 7.61280192e-02, 8.37404162e-02,
8.89634569e-02, 9.15651607e-02, 9.13586235e-02,
8.83589144e-02, 8.27804032e-02, 6.75666471e-02,
5.00483249e-02, 3.36733366e-02, 1.96758691e-02,
9.00603204e-03, 2.18370401e-03, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 2.78776980e-03,
1.05086036e-02, 2.13238822e-02, 3.45577738e-02,
4.91570145e-02, 6.36787133e-02, 7.63710088e-02,
8.54072310e-02, 8.92960200e-02, 8.75702197e-02,
8.07095447e-02, 6.97999389e-02, 5.63787286e-02,
4.20734776e-02, 2.83073312e-02, 1.61614525e-02,
6.56194125e-03, 1.00721924e-04, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
5.49667845e-03, 1.47563319e-02, 2.57955743e-02,
3.76689418e-02, 4.91861917e-02, 5.90108907e-02,
6.58478416e-02, 6.87018515e-02, 6.73174642e-02,
6.20270643e-02, 5.35456385e-02, 4.29400416e-02,
3.14129728e-02, 2.00795162e-02, 9.84001885e-03,
1.53992995e-03, 0.00000000e+00, 0.00000000e+00]]
)
np.testing.assert_allclose(fd, fd_test, rtol=1e-4)
def test_multisegment_discordant():
# The one thing that isn't check above is discordancy for segments
# with multiple quads. For this, we need a synthetic example.
x0 = np.array([0, 1, -1, 10, 9, 7])
y0 = np.array([0, 10, 20, 40, 35, 30])
z0 = np.array([0, 0, 0, 0, 0, 0])
x1 = np.array([1, -1, 0, 9, 7, 6])
y1 = np.array([10, 20, 30, 35, 30, 25])
z1 = np.array([0, 0, 0, 0, 0, 0])
x2 = np.array([3, 1, 2, 7, 5, 4])
y2 = np.array([10, 20, 30, 35, 30, 25])
z2 = np.array([10, 10, 10, 10, 10, 10])
x3 = np.array([2, 3, 1, 8, 7, 5])
y3 = np.array([0, 10, 20, 40, 35, 30])
z3 = np.array([10, 10, 10, 10, 10, 10])
epilat = 32.15270
epilon = -115.30500
proj = geo.utils.get_orthographic_projection(epilon - 1, epilon + 1,
epilat + 1, epilat - 1)
lon0, lat0 = proj(x0, y0, reverse=True)
lon1, lat1 = proj(x1, y1, reverse=True)
lon2, lat2 = proj(x2, y2, reverse=True)
lon3, lat3 = proj(x3, y3, reverse=True)
# Make an Origin object; most of the 'event' values don't matter for
# this example
origin = Origin({
'lat': 0,
'lon': 0,
'depth': 0,
'mag': 7.2,
'eventsourcecode': ''
})
rup = QuadRupture.fromVertices(lon0,
lat0,
z0,
lon1,
lat1,
z1,
lon2,
lat2,
z2,
lon3,
lat3,
z3,
origin,
group_index=[0, 0, 0, 1, 1, 1])
# Sites
buf = 0.25
lat = np.linspace(np.nanmin(rup.lats) - buf, np.nanmax(rup.lats) + buf, 20)
lon = np.linspace(np.nanmin(rup.lons) - buf, np.nanmax(rup.lons) + buf, 20)
lons, lats = np.meshgrid(lon, lat)
dep = np.zeros_like(lons)
x, y = proj(lon, lat)
rupx, rupy = proj(rup.lons, rup.lats)
# Calculate U and T
dtypes = ['U', 'T']
dists = get_distance(dtypes, lats, lons, dep, rup)
targetU = np.array(
[[
-28.53228275, -28.36479713, -28.20139732, -28.0407734,
-27.88135558, -27.72144153, -27.55935946, -27.39362017,
-27.22300147, -27.04653062, -26.86338215, -26.67275638,
-26.47381287, -26.26569449, -26.04762427, -25.81902477,
-25.57961136, -25.32943282, -25.06885791, -24.79852214
],
[
-23.53750292, -23.3748086, -23.21793537, -23.06521934,
-22.91449689, -22.76331684, -22.60928211, -22.45042208,
-22.28542121, -22.11355532, -21.93435402, -21.74720475,
-21.55115107, -21.34497916, -21.12749377, -20.89781118,
-20.6555466, -20.40086149, -20.13439948, -19.85716145
],
[
-18.53499939, -18.37689929, -18.22732841, -18.08427516,
-17.94468687, -17.80472632, -17.66045115, -17.50880802,
-17.3484421, -17.17963435, -17.0032098, -16.81921732,
-16.62638972, -16.42258419, -16.20564846, -15.9741218,
-15.72753538, -15.4663671, -15.19180844, -14.9054813
],
[
-13.52283359, -13.36797542, -13.22589288, -13.09466537,
-12.97028551, -12.84653536, -12.71591089, -12.57212088,
-12.41335561, -12.24319318, -12.06681006, -11.88598424,
-11.69798166, -11.49796348, -11.28169605, -11.04691388,
-10.79343174, -10.52262594, -10.23677602, -9.93851158
],
[
-8.49936685, -8.34357094, -8.20650964, -8.08786858, -7.98403171,
-7.88628837, -7.78005273, -7.64833307, -7.48359988, -7.29992491,
-7.11862682, -6.94410189, -6.76618701, -6.5727842, -6.35634881,
-6.11465447, -5.84925708, -5.56369035, -5.26212482, -4.94857454
],
[
-3.46638168, -3.30047216, -3.15914418, -3.04618465, -2.96252939,
-2.90194067, -2.84436315, -2.75029014, -2.56983592, -2.33744275,
-2.1512136, -1.99833104, -1.84066354, -1.6541107, -1.43071517,
-1.17252753, -0.88592286, -0.57817222, -0.25582315, 0.07585567
],
[
1.56416954, 1.75393848, 1.9183586, 2.04909316, 2.13723278,
2.17776584, 2.18272501, 2.20967639, 2.37405656, 2.65073289,
2.80205222, 2.90973407, 3.05124404, 3.2505182, 3.50336116,
3.7967575, 4.11742779, 4.45465822, 4.80070204, 5.15033407
],
[
6.5633489, 6.78740885, 6.99419348, 7.17551069, 7.31963558,
7.4113505, 7.43666779, 7.40177458, 7.40517136, 7.58520044,
7.62013169, 7.71596777, 7.90558457, 8.17213015, 8.49008681,
8.83763176, 9.19937294, 9.56556659, 9.9305469, 10.29132309
],
[
11.48996073, 11.74301446, 11.99016964, 12.22782156, 12.44984059,
12.6446727, 12.78798484, 12.82584849, 12.61992833, 12.26579742,
12.32166685, 12.54665462, 12.86628045, 13.23578462, 13.62571822,
14.01882924, 14.40617707, 14.78388296, 15.15089889, 15.5076165
],
[
16.31383216, 16.57376544, 16.83189511, 17.08626411, 17.33309437,
17.56429108, 17.76005623, 17.85853532, 17.57101025, 17.32637346,
17.45075419, 17.77199513, 18.16933168, 18.58284635, 18.9891851,
19.37985879, 19.75324557, 20.11079653, 20.4549905, 20.78837053
],
[
21.03975749, 21.28450315, 21.5243142, 21.75603974, 21.97469496,
22.17298057, 22.34310053, 22.49668569, 22.73940191, 22.70030633,
22.95351405, 23.35967832, 23.75891016, 24.14867803, 24.51536915,
24.85878249, 25.18398203, 25.49615514, 25.79932964, 26.09638269
],
[
25.70484089, 25.92709225, 26.14280395, 26.35119497, 26.55363501,
26.75827099, 26.9915523, 27.31779086, 27.77993211, 27.71070831,
28.13624949, 28.723482, 29.25285078, 29.66404032, 30.00169474,
30.30044315, 30.57916576, 30.84804427, 31.1126134, 31.37586841
],
[
30.35406633, 30.5585145, 30.75843356, 30.95627127, 31.15811912,
31.3763124, 31.63114968, 31.94156189, 32.23691802, 32.38759301,
32.86915665, 33.83467935, 34.46125278, 34.89905345, 35.25111257,
35.55095664, 35.82150686, 36.07720619, 36.32643896, 36.57385362
],
[
35.0222379, 35.21734711, 35.41081942, 35.60589495, 35.80774808,
36.02313791, 36.25826988, 36.51619168, 36.81025966, 37.21777129,
37.86674108, 38.66578072, 39.25203723, 39.78060643, 40.20815617,
40.5606039, 40.86634527, 41.14457482, 41.40732554, 41.66197722
],
[
39.73046099, 39.92514041, 40.12152415, 40.32316112, 40.5350467,
40.76393316, 41.01937758, 41.3172128, 41.68596492, 42.16604148,
42.77622755, 43.447503, 44.03771478, 44.55012468, 45.00551259,
45.40376857, 45.75505135, 46.07204699, 46.36554362, 46.64361367
],
[
44.4876174, 44.68959464, 44.89710008, 45.11420443, 45.34646809,
45.60143197, 45.88932906, 46.22363997, 46.61975585, 47.0884227,
47.62307543, 48.1913408, 48.74937117, 49.26945799, 49.74327902,
50.17123158, 50.55810895, 50.91098842, 51.23731582, 51.54375617
],
[
49.29279265, 49.50696882, 49.73006999, 49.96625305, 50.22080319,
50.50022572, 50.81209441, 51.1642666, 51.56290694, 52.00913021,
52.49553006, 53.00565389, 53.51861282, 54.01614414, 54.48672101,
54.9254339, 55.33212663, 55.70951516, 56.06170563, 56.39317058
],
[
54.13906629, 54.3671694, 54.60643024, 54.86053563, 55.13377911,
55.43088558, 55.75658576, 56.1148189, 56.50752978, 56.93329478,
57.38640012, 57.85715119, 58.33367994, 58.80451404, 59.26065475,
59.69644542, 60.10938419, 60.49940252, 60.86803179, 61.21767916
],
[
59.01741908, 59.25887491, 59.51248349, 59.78119592, 60.06816694,
60.37651862, 60.70895927, 61.0672529, 61.45160192, 61.86010542,
62.28853397, 62.73062937, 63.17894547, 63.62598375, 64.06523791,
64.49185106, 64.90281064, 65.2967858, 65.67377362, 66.03469546
],
[
63.9193099, 64.17236414, 64.4376317, 64.71732366, 65.01362255,
65.32847988, 65.66334836, 66.0188704, 66.39457546, 66.7886684,
67.19800022, 67.61828012, 68.04451487, 68.47157851, 68.89476917,
69.31022713, 69.71515194, 70.10782673, 70.4875021, 70.85420436
]])
np.testing.assert_allclose(targetU, dists['U'], atol=0.01)
targetT = np.array([
[
-2.27427469e+01, -1.97498544e+01, -1.67512900e+01, -1.37464632e+01,
-1.07350712e+01, -7.71715083e+00, -4.69305811e+00, -1.66336318e+00,
1.37131605e+00, 4.41047613e+00, 7.45381136e+00, 1.05011799e+01,
1.35524779e+01, 1.66074913e+01, 1.96657949e+01, 2.27267294e+01,
2.57894503e+01, 2.88530154e+01, 3.19164798e+01, 3.49789747e+01
],
[
-2.30778766e+01, -2.00896906e+01, -1.70950973e+01, -1.40931667e+01,
-1.10834219e+01, -8.06600712e+00, -5.04171582e+00, -2.01179123e+00,
1.02248614e+00, 4.06025218e+00, 7.10129626e+00, 1.01459367e+01,
1.31946312e+01, 1.62475702e+01, 1.93044511e+01, 2.23644788e+01,
2.54265185e+01, 2.84892997e+01, 3.15515954e+01, 3.46123426e+01
],
[
-2.33971472e+01, -2.04144525e+01, -1.74245193e+01, -1.44256870e+01,
-1.14169177e+01, -8.39830615e+00, -5.37141115e+00, -2.33902937e+00,
6.95823925e-01, 3.73133431e+00, 6.76769593e+00, 9.80663091e+00,
1.28500821e+01, 1.58991008e+01, 1.89534737e+01, 2.20119662e+01,
2.50728111e+01, 2.81341606e+01, 3.11943854e+01, 3.42522163e+01
],
[
-2.36965870e+01, -2.07206976e+01, -1.77370901e+01, -1.47426715e+01,
-1.17347885e+01, -8.71247709e+00, -5.67801094e+00, -2.63761285e+00,
4.00625914e-01, 3.43182302e+00, 6.45782532e+00, 9.48491128e+00,
1.25187545e+01, 1.55616657e+01, 1.86127822e+01, 2.16694756e+01,
2.47286680e+01, 2.77876297e+01, 3.08443066e+01, 3.38973527e+01
],
[
-2.39698399e+01, -2.10022612e+01, -1.80281475e+01, -1.50423801e+01,
-1.20388157e+01, -9.01204040e+00, -5.96160398e+00, -2.89867328e+00,
1.52194374e-01, 3.17268218e+00, 6.17334725e+00, 9.17699572e+00,
1.21964990e+01, 1.52330975e+01, 1.82821226e+01, 2.13375815e+01,
2.43943933e+01, 2.74490375e+01, 3.04994435e+01, 3.35446330e+01
],
[
-2.42070742e+01, -2.12471979e+01, -1.82855675e+01, -1.53163304e+01,
-1.23296744e+01, -9.31127857e+00, -6.24535210e+00, -3.12882361e+00,
-2.24460581e-02, 2.95354485e+00, 5.89215412e+00, 8.86387424e+00,
1.18748249e+01, 1.49128245e+01, 1.79640055e+01, 2.10182501e+01,
2.40696313e+01, 2.71153177e+01, 3.01543919e+01, 3.31869788e+01
],
[
-2.43971375e+01, -2.14368866e+01, -1.84826148e+01, -1.55321207e+01,
-1.25786621e+01, -9.60654678e+00, -6.58612151e+00, -3.48118311e+00,
-3.16555025e-01, 2.61618307e+00, 5.53740540e+00, 8.52666510e+00,
1.15623361e+01, 1.46149780e+01, 1.76674294e+01, 2.07125025e+01,
2.37483764e+01, 2.67756033e+01, 2.97955606e+01, 3.28097430e+01
],
[
-2.45384925e+01, -2.15583842e+01, -1.85874288e+01, -1.56290738e+01,
-1.26867853e+01, -9.76140655e+00, -6.84407754e+00, -3.90089971e+00,
-8.41806596e-01, 2.14754495e+00, 5.18583472e+00, 8.26271822e+00,
1.13266091e+01, 1.43684333e+01, 1.73916223e+01, 2.04017469e+01,
2.34034936e+01, 2.64002111e+01, 2.93941282e+01, 3.23866586e+01
],
[
-2.46576775e+01, -2.16355610e+01, -1.86129545e+01, -1.55919156e+01,
-1.25763765e+01, -9.57306672e+00, -6.59044329e+00, -3.62352541e+00,
-5.92041388e-01, 2.33255341e+00, 5.29498494e+00, 8.24834463e+00,
1.11833819e+01, 1.41167617e+01, 1.70571082e+01, 2.00065102e+01,
2.29645946e+01, 2.59302937e+01, 2.89023967e+01, 3.18797332e+01
],
[
-2.48161623e+01, -2.17489533e+01, -1.86651328e+01, -1.55589864e+01,
-1.24224388e+01, -9.24466730e+00, -6.01521475e+00, -2.75148770e+00,
3.89519039e-01, 2.99589525e+00, 5.45696689e+00, 8.01247078e+00,
1.07291540e+01, 1.35565782e+01, 1.64461360e+01, 1.93723515e+01,
2.23222250e+01, 2.52881249e+01, 2.82650171e+01, 3.12494172e+01
],
[
-2.50857405e+01, -2.20002811e+01, -1.88926336e+01, -1.57550887e+01,
-1.25770789e+01, -9.34497451e+00, -6.04430316e+00, -2.67290100e+00,
5.40854953e-01, 2.30509492e+00, 3.58183843e+00, 6.23701436e+00,
9.28727128e+00, 1.23205706e+01, 1.53428945e+01, 1.83666035e+01,
2.13934954e+01, 2.44218171e+01, 2.74496472e+01, 3.04757209e+01
],
[
-2.55082697e+01, -2.24454912e+01, -1.93710045e+01, -1.62824768e+01,
-1.31767102e+01, -1.00469827e+01, -6.86985653e+00, -3.54681638e+00,
1.07062999e-01, 3.34891657e-01, -1.70694750e-01, 3.57896940e+00,
7.17013928e+00, 1.05232789e+01, 1.37976070e+01, 1.70230221e+01,
2.02076136e+01, 2.33576919e+01, 2.64794914e+01, 2.95785985e+01
],
[
-2.60778515e+01, -2.30695744e+01, -2.00684150e+01, -1.70790651e+01,
-1.41074315e+01, -1.11587507e+01, -8.23273307e+00, -5.33306966e+00,
-2.80144302e+00, -1.84760416e+00, -1.05368779e+00, 1.26163211e+00,
4.90086292e+00, 8.53883059e+00, 1.20996577e+01, 1.55589098e+01,
1.89237978e+01, 2.22114952e+01, 2.54390313e+01, 2.86203790e+01
],
[
-2.67537229e+01, -2.38123298e+01, -2.08964272e+01, -1.80168638e+01,
-1.51896230e+01, -1.24401995e+01, -9.81536176e+00, -7.41008520e+00,
-5.38073414e+00, -3.78262975e+00, -2.29669890e+00, -3.53057240e-01,
3.13642477e+00, 6.97021789e+00, 1.07026969e+01, 1.42945488e+01,
1.77655640e+01, 2.11406146e+01, 2.44409375e+01, 2.76832489e+01
],
[
-2.74832153e+01, -2.46028623e+01, -2.17593854e+01, -1.89653378e+01,
-1.62381218e+01, -1.36022404e+01, -1.10914555e+01, -8.74572618e+00,
-6.58963863e+00, -4.58336507e+00, -2.57607747e+00, -2.67233150e-01,
2.82788692e+00, 6.36737407e+00, 9.93334021e+00, 1.34440609e+01,
1.68846862e+01, 2.02577163e+01, 2.35710668e+01, 2.68337230e+01
],
[
-2.82199728e+01, -2.53838486e+01, -2.25869234e+01, -1.98388981e+01,
-1.71512612e+01, -1.45365893e+01, -1.20059297e+01, -9.56220853e+00,
-7.18799023e+00, -4.83006994e+00, -2.39120744e+00, 2.51308627e-01,
3.17331949e+00, 6.33022626e+00, 9.61428455e+00, 1.29426788e+01,
1.62705993e+01, 1.95770961e+01, 2.28539081e+01, 2.60992146e+01
],
[
-2.89332200e+01, -2.61222251e+01, -2.33461951e+01, -2.06105222e+01,
-1.79200485e+01, -1.52776479e+01, -1.26817390e+01, -1.01225741e+01,
-7.57801870e+00, -5.01122873e+00, -2.37434916e+00, 3.78303328e-01,
3.27093827e+00, 6.29527723e+00, 9.41912399e+00, 1.26046423e+01,
1.58204753e+01, 1.90448689e+01, 2.22643265e+01, 2.54712657e+01
],
[
-2.96082809e+01, -2.68067500e+01, -2.40331802e+01, -2.12894659e+01,
-1.85760763e+01, -1.58910124e+01, -1.32284735e+01, -1.05774862e+01,
-7.92111801e+00, -5.23724922e+00, -2.50179068e+00, 3.05790568e-01,
3.19666197e+00, 6.16975035e+00, 9.21353475e+00, 1.23109519e+01,
1.54443017e+01, 1.85982825e+01, 2.17611016e+01, 2.49243957e+01
],
[
-3.02420504e+01, -2.74395034e+01, -2.46578094e+01, -2.18967353e+01,
-1.91546206e+01, -1.64278219e+01, -1.37101816e+01, -1.09927140e+01,
-8.26378719e+00, -5.51007519e+00, -2.71836365e+00, 1.22111758e-01,
3.01754598e+00, 5.96851903e+00, 8.97043180e+00, 1.20150997e+01,
1.50927299e+01, 1.81935916e+01, 2.13090724e+01, 2.44321477e+01
],
[
-3.08377073e+01, -2.80281994e+01, -2.52335334e+01, -2.24524366e+01,
-1.96825082e+01, -1.69199811e+01, -1.41595768e+01, -1.13945492e+01,
-8.61701306e+00, -5.81861191e+00, -2.99148017e+00, -1.29317230e-01,
2.77170749e+00, 5.71249079e+00, 8.69110042e+00, 1.17033684e+01,
1.47437429e+01, 1.78061436e+01, 2.08846464e+01, 2.39739290e+01
]
])
np.testing.assert_allclose(targetT, dists['T'], atol=0.01)
def test_ss3_m6():
magnitude = 6.0
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin:
origin = Origin({
'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake
})
rup = QuadRupture.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
origin,
reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array([[
0.05853668, 0.05032323, 0.0306438, 0.00839635, -0.01102162, -0.02621319
],
[
0.01720501, -0.00687296, -0.03804823, -0.05547473,
-0.0644932, -0.06947135
],
[
-0.03000065, -0.07006634, -0.07708165, -0.07865941,
-0.0792369, -0.07950887
],
[
0.0398062, 0.02571145, -0.0018651, -0.0255418,
-0.04176278, -0.05235095
],
[
0.0696989, 0.06389524, 0.04890304, 0.02983134,
0.01098535, -0.00545921
],
[
0.088278, 0.08511069, 0.07628596, 0.06350294,
0.04875897, 0.03373495
],
[
0.10179334, 0.09978475, 0.09401676, 0.0851842,
0.07422509, 0.06210369
],
[
0.11242209, 0.11102701, 0.10696056, 0.10055471,
0.09229027, 0.08271454
],
[
0.12118279, 0.12015315, 0.11712653, 0.11228058,
0.10588323, 0.09825795
],
[
0.12785957, 0.12706892, 0.12473264, 0.12095384,
0.11589197, 0.10974684
],
[
0.12785908, 0.12724852, 0.12543819, 0.12249026,
0.11850249, 0.11360047
]])
np.testing.assert_allclose(fd, fd_test, rtol=1e-4)
def test_ss3():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin:
origin = Origin({'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake})
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='ss3')
x = np.linspace(-60, 60, 21)
y = np.linspace(-60, 138, 34)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[0.00000000e+00, 0.00000000e+00, 2.14620746e-03,
6.47899336e-03, 1.23119791e-02, 1.91676140e-02,
2.64009788e-02, 3.32427846e-02, 3.88863288e-02,
4.26104002e-02, 4.39120296e-02, 4.26104002e-02,
3.88863288e-02, 3.32427846e-02, 2.64009788e-02,
1.91676140e-02, 1.23119791e-02, 6.47899336e-03,
2.14620746e-03, 0.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 8.57780996e-04, 3.99405791e-03,
9.31948105e-03, 1.65406113e-02, 2.51316805e-02,
3.43205435e-02, 4.31274592e-02, 5.04747209e-02,
5.53634169e-02, 5.70796092e-02, 5.53634169e-02,
5.04747209e-02, 4.31274592e-02, 3.43205435e-02,
2.51316805e-02, 1.65406113e-02, 9.31948105e-03,
3.99405791e-03, 8.57780996e-04, 0.00000000e+00],
[-7.32594549e-04, 1.80425497e-04, 3.76908220e-03,
1.00175179e-02, 1.86854835e-02, 2.92291145e-02,
4.07487277e-02, 5.20057177e-02, 6.15509770e-02,
6.79776087e-02, 7.02477931e-02, 6.79776087e-02,
6.15509770e-02, 5.20057177e-02, 4.07487277e-02,
2.92291145e-02, 1.86854835e-02, 1.00175179e-02,
3.76908220e-03, 1.80425497e-04, -7.32594549e-04],
[-3.29238561e-03, -2.60643191e-03, 1.16635260e-03,
8.15185259e-03, 1.82290773e-02, 3.08983182e-02,
4.51608038e-02, 5.94769126e-02, 7.18919113e-02,
8.03888307e-02, 8.34165399e-02, 8.03888307e-02,
7.18919113e-02, 5.94769126e-02, 4.51608038e-02,
3.08983182e-02, 1.82290773e-02, 8.15185259e-03,
1.16635260e-03, -2.60643191e-03, -3.29238561e-03],
[-7.68543266e-03, -7.63179286e-03, -4.08866637e-03,
3.27605236e-03, 1.45558215e-02, 2.94068040e-02,
4.68176355e-02, 6.49397159e-02, 7.72066272e-02,
8.50445368e-02, 8.77974692e-02, 8.50445368e-02,
7.72066272e-02, 6.49397159e-02, 4.68176355e-02,
2.94068040e-02, 1.45558215e-02, 3.27605236e-03,
-4.08866637e-03, -7.63179286e-03, -7.68543266e-03],
[-1.38078234e-02, -1.49011067e-02, -1.21731364e-02,
-5.02168047e-03, 6.98177526e-03, 2.38268531e-02,
4.30419205e-02, 6.00041964e-02, 7.44541603e-02,
8.42939552e-02, 8.77989590e-02, 8.42939552e-02,
7.44541603e-02, 6.00041964e-02, 4.30419205e-02,
2.38268531e-02, 6.98177526e-03, -5.02168047e-03,
-1.21731364e-02, -1.49011067e-02, -1.38078234e-02],
[-2.13780396e-02, -2.42165379e-02, -2.30613142e-02,
-1.70011475e-02, -5.15036128e-03, 1.25885635e-02,
3.24536739e-02, 5.25619351e-02, 7.05100243e-02,
8.31900906e-02, 8.78003567e-02, 8.31900906e-02,
7.05100243e-02, 5.25619351e-02, 3.24536739e-02,
1.25885635e-02, -5.15036128e-03, -1.70011475e-02,
-2.30613142e-02, -2.42165379e-02, -2.13780396e-02],
[-2.98882710e-02, -3.50862342e-02, -3.63793490e-02,
-3.25716319e-02, -2.22546618e-02, -3.59274163e-03,
1.83064517e-02, 4.20112440e-02, 6.46115966e-02,
8.14746164e-02, 8.78016623e-02, 8.14746164e-02,
6.46115966e-02, 4.20112440e-02, 1.83064517e-02,
-3.59274163e-03, -2.22546618e-02, -3.25716319e-02,
-3.63793490e-02, -3.50862342e-02, -2.98882710e-02],
[-3.85810679e-02, -4.66488633e-02, -5.12430987e-02,
-5.10089462e-02, -4.20856023e-02, -2.36905234e-02,
-6.33876287e-04, 2.66765430e-02, 5.53289928e-02,
7.86066125e-02, 8.78028757e-02, 7.86066125e-02,
5.53289928e-02, 2.66765430e-02, -6.33876287e-04,
-2.36905234e-02, -4.20856023e-02, -5.10089462e-02,
-5.12430987e-02, -4.66488633e-02, -3.85810679e-02],
[-4.64803335e-02, -5.76615888e-02, -6.61458422e-02,
-7.06512643e-02, -6.38427394e-02, -4.77258398e-02,
-2.55483969e-02, 4.05840724e-03, 3.98470070e-02,
7.33053399e-02, 8.78039969e-02, 7.33053399e-02,
3.98470070e-02, 4.05840724e-03, -2.55483969e-02,
-4.77258398e-02, -6.38427394e-02, -7.06512643e-02,
-6.61458422e-02, -5.76615888e-02, -4.64803335e-02],
[-5.25038299e-02, -6.66129442e-02, -7.90147081e-02,
-8.87629178e-02, -8.59653118e-02, -7.42828398e-02,
-5.64316505e-02, -2.87083225e-02, 1.25945312e-02,
6.19971667e-02, 8.78050260e-02, 6.19971667e-02,
1.25945312e-02, -2.87083225e-02, -5.64316505e-02,
-7.42828398e-02, -8.59653118e-02, -8.87629178e-02,
-7.90147081e-02, -6.66129442e-02, -5.25038299e-02],
[-5.69779111e-02, -7.36791817e-02, -8.97495345e-02,
-1.04799583e-01, -1.07737239e-01, -1.02875880e-01,
-9.46568471e-02, -7.95630162e-02, -4.96285112e-02,
6.59954795e-03, 5.25569882e-02, 6.59954795e-03,
-4.96285112e-02, -7.95630162e-02, -9.46568471e-02,
-1.02875880e-01, -1.07737239e-01, -1.04799583e-01,
-8.97495345e-02, -7.36791817e-02, -5.69779111e-02],
[-5.90357675e-02, -7.69727119e-02, -9.48442826e-02,
-1.12607620e-01, -1.18744885e-01, -1.18201834e-01,
-1.17217017e-01, -1.15152899e-01, -1.09694433e-01,
-8.82341332e-02, -1.61624035e-02, -8.82341332e-02,
-1.09694433e-01, -1.15152899e-01, -1.17217017e-01,
-1.18201834e-01, -1.18744885e-01, -1.12607620e-01,
-9.48442826e-02, -7.69727119e-02, -5.90357675e-02],
[-5.92189452e-02, -7.72680305e-02, -9.53051857e-02,
-1.13322519e-01, -1.19770917e-01, -1.19670660e-01,
-1.19486798e-01, -1.19092639e-01, -1.17989113e-01,
-1.12555820e-01, -4.50009776e-02, -1.12555820e-01,
-1.17989113e-01, -1.19092639e-01, -1.19486798e-01,
-1.19670660e-01, -1.19770917e-01, -1.13322519e-01,
-9.53051857e-02, -7.72680305e-02, -5.92189452e-02],
[-5.79249958e-02, -7.51927112e-02, -9.20842554e-02,
-1.08361430e-01, -1.12722790e-01, -1.09732675e-01,
-1.04531672e-01, -9.44729544e-02, -7.23277773e-02,
-2.05699911e-02, 3.58249631e-02, -2.05699911e-02,
-7.23277773e-02, -9.44729544e-02, -1.04531672e-01,
-1.09732675e-01, -1.12722790e-01, -1.08361430e-01,
-9.20842554e-02, -7.51927112e-02, -5.79249958e-02],
[-5.42527703e-02, -6.93641123e-02, -8.31684773e-02,
-9.49114165e-02, -9.41989454e-02, -8.48645354e-02,
-7.00894708e-02, -4.58286259e-02, -6.37563061e-03,
4.68887998e-02, 7.77968419e-02, 4.68887998e-02,
-6.37563061e-03, -4.58286259e-02, -7.00894708e-02,
-8.48645354e-02, -9.41989454e-02, -9.49114165e-02,
-8.31684773e-02, -6.93641123e-02, -5.42527703e-02],
[-4.82490057e-02, -5.99997941e-02, -6.91786120e-02,
-7.44891242e-02, -6.73705808e-02, -5.13001284e-02,
-2.84188057e-02, 3.60143816e-03, 4.47470123e-02,
8.58663851e-02, 1.04548354e-01, 8.58663851e-02,
4.47470123e-02, 3.60143816e-03, -2.84188057e-02,
-5.13001284e-02, -6.73705808e-02, -7.44891242e-02,
-6.91786120e-02, -5.99997941e-02, -4.82490057e-02],
[-4.03203010e-02, -4.79063206e-02, -5.16352259e-02,
-4.98707253e-02, -3.67295509e-02, -1.57342058e-02,
1.13668830e-02, 4.46551184e-02, 8.10450840e-02,
1.11780747e-01, 1.24226598e-01, 1.11780747e-01,
8.10450840e-02, 4.46551184e-02, 1.13668830e-02,
-1.57342058e-02, -3.67295509e-02, -4.98707253e-02,
-5.16352259e-02, -4.79063206e-02, -4.03203010e-02],
[-3.10250239e-02, -3.40796094e-02, -3.22089254e-02,
-2.37094100e-02, -5.85463114e-03, 1.77402761e-02,
4.57786845e-02, 7.69637052e-02, 1.07537652e-01,
1.30906328e-01, 1.39800436e-01, 1.30906328e-01,
1.07537652e-01, 7.69637052e-02, 4.57786845e-02,
1.77402761e-02, -5.85463114e-03, -2.37094100e-02,
-3.22089254e-02, -3.40796094e-02, -3.10250239e-02],
[-2.09301700e-02, -1.94475962e-02, -1.22970199e-02,
2.07296407e-03, 2.31516868e-02, 4.74574033e-02,
7.44743481e-02, 1.02380049e-01, 1.27776301e-01,
1.46003379e-01, 1.52690015e-01, 1.46003379e-01,
1.27776301e-01, 1.02380049e-01, 7.44743481e-02,
4.74574033e-02, 2.31516868e-02, 2.07296407e-03,
-1.22970199e-02, -1.94475962e-02, -2.09301700e-02],
[-1.05257992e-02, -4.74329696e-03, 7.12107274e-03,
2.63431361e-02, 4.93709790e-02, 7.31527220e-02,
9.82233938e-02, 1.22728059e-01, 1.43894925e-01,
1.58465026e-01, 1.63685984e-01, 1.58465026e-01,
1.43894925e-01, 1.22728059e-01, 9.82233938e-02,
7.31527220e-02, 4.93709790e-02, 2.63431361e-02,
7.12107274e-03, -4.74329696e-03, -1.05257992e-02],
[-1.89098657e-04, 9.52392382e-03, 2.54577716e-02,
4.85730869e-02, 7.26048516e-02, 9.51726659e-02,
1.17988523e-01, 1.39380421e-01, 1.57176612e-01,
1.69076915e-01, 1.73274075e-01, 1.69076915e-01,
1.57176612e-01, 1.39380421e-01, 1.17988523e-01,
9.51726659e-02, 7.26048516e-02, 4.85730869e-02,
2.54577716e-02, 9.52392382e-03, -1.89098657e-04],
[9.81732797e-03, 2.30419581e-02, 4.24234701e-02,
6.86213308e-02, 9.30164618e-02, 1.14050063e-01,
1.34620894e-01, 1.53304069e-01, 1.68420867e-01,
1.78321253e-01, 1.81774183e-01, 1.78321253e-01,
1.68420867e-01, 1.53304069e-01, 1.34620894e-01,
1.14050063e-01, 9.30164618e-02, 6.86213308e-02,
4.24234701e-02, 2.30419581e-02, 9.81732797e-03],
[1.93290725e-02, 3.56493099e-02, 5.79271157e-02,
8.65611122e-02, 1.10914315e-01, 1.30317702e-01,
1.48798006e-01, 1.65173224e-01, 1.78147031e-01,
1.86513895e-01, 1.89408199e-01, 1.86513895e-01,
1.78147031e-01, 1.65173224e-01, 1.48798006e-01,
1.30317702e-01, 1.10914315e-01, 8.65611122e-02,
5.79271157e-02, 3.56493099e-02, 1.93290725e-02],
[2.68168937e-02, 4.52356810e-02, 6.92261217e-02,
9.89630241e-02, 1.23093435e-01, 1.40640067e-01,
1.56998943e-01, 1.71215219e-01, 1.82297185e-01,
1.89360704e-01, 1.91789146e-01, 1.89360704e-01,
1.82297185e-01, 1.71215219e-01, 1.56998943e-01,
1.40640067e-01, 1.23093435e-01, 9.89630241e-02,
6.92261217e-02, 4.52356810e-02, 2.68168937e-02],
[3.19403269e-02, 5.15051953e-02, 7.61032066e-02,
1.05705197e-01, 1.31722206e-01, 1.47466588e-01,
1.61892450e-01, 1.74235616e-01, 1.83735386e-01,
1.89735533e-01, 1.91788616e-01, 1.89735533e-01,
1.83735386e-01, 1.74235616e-01, 1.61892450e-01,
1.47466588e-01, 1.31722206e-01, 1.05705197e-01,
7.61032066e-02, 5.15051953e-02, 3.19403269e-02],
[3.48604070e-02, 5.49292382e-02, 7.94274234e-02,
1.08149011e-01, 1.38923419e-01, 1.53070440e-01,
1.65849067e-01, 1.76646162e-01, 1.84871647e-01,
1.90029617e-01, 1.91787948e-01, 1.90029617e-01,
1.84871647e-01, 1.76646162e-01, 1.65849067e-01,
1.53070440e-01, 1.38923419e-01, 1.08149011e-01,
7.94274234e-02, 5.49292382e-02, 3.48604070e-02],
[3.53402022e-02, 5.53653759e-02, 7.91965502e-02,
1.06486934e-01, 1.36563003e-01, 1.57713955e-01,
1.69087164e-01, 1.78598269e-01, 1.85784340e-01,
1.90264452e-01, 1.91787141e-01, 1.90264452e-01,
1.85784340e-01, 1.78598269e-01, 1.69087164e-01,
1.57713955e-01, 1.36563003e-01, 1.06486934e-01,
7.91965502e-02, 5.53653759e-02, 3.53402022e-02],
[3.32889822e-02, 5.28319225e-02, 7.55769079e-02,
1.01077605e-01, 1.28592068e-01, 1.57023616e-01,
1.71766715e-01, 1.80199729e-01, 1.86528091e-01,
1.90454829e-01, 1.91786196e-01, 1.90454829e-01,
1.86528091e-01, 1.80199729e-01, 1.71766715e-01,
1.57023616e-01, 1.28592068e-01, 1.01077605e-01,
7.55769079e-02, 5.28319225e-02, 3.32889822e-02],
[2.87295370e-02, 4.74613283e-02, 6.88388861e-02,
9.23568989e-02, 1.17254645e-01, 1.42483223e-01,
1.66695764e-01, 1.81528776e-01, 1.87141877e-01,
1.90611190e-01, 1.91785112e-01, 1.90611190e-01,
1.87141877e-01, 1.81528776e-01, 1.66695764e-01,
1.42483223e-01, 1.17254645e-01, 9.23568989e-02,
6.88388861e-02, 4.74613283e-02, 2.87295370e-02],
[2.17650266e-02, 3.94568191e-02, 5.93023344e-02,
8.07720575e-02, 1.03124482e-01, 1.25394282e-01,
1.46405870e-01, 1.64828303e-01, 1.79288925e-01,
1.88553222e-01, 1.91747252e-01, 1.88553222e-01,
1.79288925e-01, 1.64828303e-01, 1.46405870e-01,
1.25394282e-01, 1.03124482e-01, 8.07720575e-02,
5.93023344e-02, 3.94568191e-02, 2.17650266e-02],
[1.25495284e-02, 2.90572166e-02, 4.72972116e-02,
6.67423656e-02, 8.66951873e-02, 1.06290296e-01,
1.24520131e-01, 1.40293247e-01, 1.52531693e-01,
1.60303860e-01, 1.62970689e-01, 1.60303860e-01,
1.52531693e-01, 1.40293247e-01, 1.24520131e-01,
1.06290296e-01, 8.66951873e-02, 6.67423656e-02,
4.72972116e-02, 2.90572166e-02, 1.25495284e-02],
[1.26441934e-03, 1.65114811e-02, 3.31390978e-02,
5.06407706e-02, 6.83765492e-02, 8.55839448e-02,
1.01408074e-01, 1.14955639e-01, 1.25373662e-01,
1.31946425e-01, 1.34193829e-01, 1.31946425e-01,
1.25373662e-01, 1.14955639e-01, 1.01408074e-01,
8.55839448e-02, 6.83765492e-02, 5.06407706e-02,
3.31390978e-02, 1.65114811e-02, 1.26441934e-03],
[0.00000000e+00, 2.06213867e-03, 1.71162845e-02,
3.27888240e-02, 4.85026462e-02, 6.35932476e-02,
7.73387997e-02, 8.90069217e-02, 9.79166934e-02,
1.03509489e-01, 1.05416736e-01, 1.03509489e-01,
9.79166934e-02, 8.90069217e-02, 7.73387997e-02,
6.35932476e-02, 4.85026462e-02, 3.27888240e-02,
1.71162845e-02, 2.06213867e-03, 0.00000000e+00]]
)
np.testing.assert_allclose(fd, fd_test, rtol=1e-4)
def test_rv4():
magnitude = 7.0
rake = 90.0
width = np.array([28])
rupx = np.array([0, 0])
rupy = np.array([0, 32])
zp = np.array([0])
dip = np.array([30])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
# Dummy Origin
origin = Origin({
'lat': 0,
'lon': 0,
'depth': 0,
'mag': 0,
'eventsourcecode': 'rv4',
'rake': rake
})
# Rupture
rup = QuadRupture.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
origin,
reference='')
L = rup.getLength()
# Figure out epicenter
tmp = rup.getQuadrilaterals()[0]
pp0 = Vector.fromPoint(
point.Point(tmp[0].longitude, tmp[0].latitude, tmp[0].depth))
pp1 = Vector.fromPoint(
point.Point(tmp[1].longitude, tmp[1].latitude, tmp[1].depth))
pp2 = Vector.fromPoint(
point.Point(tmp[2].longitude, tmp[2].latitude, tmp[2].depth))
pp3 = Vector.fromPoint(
point.Point(tmp[3].longitude, tmp[3].latitude, tmp[3].depth))
dxp = 6 / L
dyp = (width - 8) / width
mp0 = pp0 + (pp1 - pp0) * dxp
mp1 = pp3 + (pp2 - pp3) * dxp
rp = mp0 + (mp1 - mp0) * dyp
epilat, epilon, epidepth = ecef2latlon(rp.x, rp.y, rp.z)
# Fix Origin:
origin = Origin({
'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'eventsourcecode': 'rv4',
'rake': rake
})
x = np.linspace(-50, 50, 11)
y = np.linspace(-50, 50, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=2.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[
0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 1.72143257e-03,
1.34977260e-03, 4.33616224e-15, 1.24446253e-03, 1.16142357e-03,
2.25464716e-03, 7.05281751e-04, 0.00000000e+00
],
[
0.00000000e+00, 0.00000000e+00, 7.62610242e-03, 1.25133844e-02,
5.61896104e-03, 7.63126014e-15, 4.52266194e-03, 4.67970900e-03,
1.02820316e-02, 5.13160096e-03, -6.13926251e-03
],
[
0.00000000e+00, 4.00495234e-03, 2.37608386e-02, 2.37139333e-02,
9.55224050e-03, 5.66364910e-15, 7.70344813e-03, 7.36466362e-03,
1.48239704e-02, 8.40388145e-03, -1.58592485e-02
],
[
8.08385547e-19, 9.38150101e-03, 3.38610620e-02, 3.85351492e-02,
1.91044918e-02, 3.98697802e-15, 1.54321666e-02, 1.21913760e-02,
2.04435166e-02, 1.04931859e-02, -1.85935894e-02
],
[
2.12025421e-18, 1.37316085e-02, 4.40193799e-02, 6.16562477e-02,
4.77612496e-02, 2.60257085e-15, 3.86322888e-02, 1.97965887e-02,
2.64882038e-02, 1.23335908e-02, -2.07389932e-02
],
[
2.64338576e-18, 1.45898292e-02, 4.89104213e-02, 7.70703166e-02,
9.55225258e-02, 1.01875104e-01, 7.73459329e-02, 2.50275508e-02,
2.93537540e-02, 1.30949577e-02, -2.15685454e-02
],
[
2.64330042e-18, 1.45898262e-02, 4.89104186e-02, 7.70703146e-02,
9.55225248e-02, 1.01910945e-01, 7.74050835e-02, 2.52307946e-02,
2.92970736e-02, 1.30880504e-02, -2.15685424e-02
],
[
2.64318867e-18, 1.45898259e-02, 4.89104184e-02, 7.70703144e-02,
9.55225247e-02, 1.01933432e-01, 7.74421258e-02, 2.53572923e-02,
2.92615130e-02, 1.30837284e-02, -2.15685422e-02
],
[
2.64305117e-18, 1.45898284e-02, 4.89104206e-02, 7.70703161e-02,
9.55225256e-02, 1.01942593e-01, 7.74571359e-02, 2.54081640e-02,
2.92472117e-02, 1.30819985e-02, -2.15685446e-02
],
[
2.30141673e-18, 1.40210825e-02, 4.56205547e-02, 6.63109661e-02,
5.79266964e-02, 2.33044622e-15, 4.69672564e-02, 2.18401553e-02,
2.72864925e-02, 1.25728575e-02, -2.10227772e-02
],
[
1.10672535e-18, 1.04777076e-02, 3.59041065e-02, 4.24614318e-02,
2.24217216e-02, 3.66914762e-15, 1.81728517e-02, 1.39301504e-02,
2.14956836e-02, 1.08711460e-02, -1.90802849e-02
]])
np.testing.assert_allclose(fd, fd_test, rtol=2e-4)
def test_ss3_m6():
magnitude = 6.0
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * rupy[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin:
origin = Origin({'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake})
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[0.05853668, 0.05032323, 0.0306438, 0.00839635, -0.01102162,
-0.02621319],
[0.01720501, -0.00687296, -0.03804823, -0.05547473, -0.0644932,
-0.06947135],
[-0.03000065, -0.07006634, -0.07708165, -0.07865941, -0.0792369,
-0.07950887],
[0.0398062, 0.02571145, -0.0018651, -0.0255418, -0.04176278,
-0.05235095],
[0.0696989, 0.06389524, 0.04890304, 0.02983134, 0.01098535,
-0.00545921],
[0.088278, 0.08511069, 0.07628596, 0.06350294, 0.04875897,
0.03373495],
[0.10179334, 0.09978475, 0.09401676, 0.0851842, 0.07422509,
0.06210369],
[0.11242209, 0.11102701, 0.10696056, 0.10055471, 0.09229027,
0.08271454],
[0.12118279, 0.12015315, 0.11712653, 0.11228058, 0.10588323,
0.09825795],
[0.12785957, 0.12706892, 0.12473264, 0.12095384, 0.11589197,
0.10974684],
[0.12785908, 0.12724852, 0.12543819, 0.12249026, 0.11850249,
0.11360047]])
np.testing.assert_allclose(
fd, fd_test, rtol=1e-4)
def test_ss3_move_hypo1():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
rupx = np.array([0, 0])
rupy = np.array([0, 80])
zp = np.array([0.0])
epix = np.array([1.0])
epiy = np.array([-1.0])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
# Origin
origin = Origin({'lat': epilat[0],
'lon': epilon[0],
'depth': -1,
'mag': magnitude,
'eventsourcecode': 'ss3',
'rake': rake})
rup = QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, origin, reference='ss3')
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
phyp = copy.deepcopy(test1.phyp[0])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.004233219183604, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989205968, rtol=1e-4)
# --------------------------------------------------------------------------
# Also for multiple segments
# --------------------------------------------------------------------------
dip = np.array([90., 90., 90.])
rake = 180.0
width = np.array([15., 15., 10.])
rupx = np.array([0., 0., 10., 20.])
rupy = np.array([0., 20., 60., 80.])
zp = np.array([0., 0., 0.])
epix = np.array([0.])
epiy = np.array([0.])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(rupx, rupy, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
rup = QuadRupture.fromTrace(
np.array(tlon[0:3]), np.array(tlat[0:3]),
np.array(tlon[1:4]), np.array(tlat[1:4]),
zp, width, dip, origin, reference='')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': 1.0,
'mag': magnitude,
'eventsourcecode': '',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = HistoricTime.utcfromtimestamp(int(time.time()))
event['created'] = HistoricTime.utcfromtimestamp(int(time.time()))
x = np.linspace(0, 20, 6)
y = np.linspace(0, 90, 11)
site_x, site_y = np.meshgrid(x, y)
slon, slat = proj(site_x, site_y, reverse=True)
deps = np.zeros_like(slon)
origin = Origin(event)
origin.rake = rake
test1 = Bayless2013(origin, rup, slat, slon, deps, T=1.0)
# 1st pseudo-hyp
phyp = copy.deepcopy(test1.phyp[0])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.004233219183604, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989205968, rtol=1e-4)
# 2nd pseudo-hyp
phyp = copy.deepcopy(test1.phyp[1])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.184097835787796, rtol=1e-4)
np.testing.assert_allclose(plon, -120.98636122402166, rtol=1e-4)
np.testing.assert_allclose(pdep, 7.4999999989103525, rtol=1e-4)
# 3rd pseudo-hyp
phyp = copy.deepcopy(test1.phyp[2])
plat, plon, pdep = ecef2latlon(phyp.x, phyp.y, phyp.z)
px, py = proj(plon, plat, reverse=False)
np.testing.assert_allclose(plat, 38.543778594535752, rtol=1e-4)
np.testing.assert_allclose(plon, -120.87137783362499, rtol=1e-4)
np.testing.assert_allclose(pdep, 4.9999999995063993, rtol=1e-4)
def test_rupture_depth(interactive=False):
DIP = 17.0
WIDTH = 20.0
GRIDRES = 0.1
names = ['single', 'double', 'triple',
'concave', 'concave_simple', 'ANrvSA']
means = [3.1554422780092461, 2.9224454569459781,
3.0381968625073563, 2.0522694624400271,
2.4805390352818755, 2.8740121776209673]
stds = [2.1895293825074575, 2.0506459673526174,
2.0244588429154402, 2.0112565876976416,
2.1599789955270019, 1.6156220309120068]
xp0list = [np.array([118.3]),
np.array([10.1, 10.1]),
np.array([10.1, 10.1, 10.3]),
np.array([10.9, 10.5, 10.9]),
np.array([10.9, 10.6]),
np.array([-76.483, -76.626, -76.757, -76.99, -77.024, -76.925,
-76.65, -76.321, -75.997, -75.958])]
xp1list = [np.array([118.3]),
np.array([10.1, 10.3]),
np.array([10.1, 10.3, 10.1]),
np.array([10.5, 10.9, 11.3]),
np.array([10.6, 10.9]),
np.array([-76.626, -76.757, -76.99, -77.024, -76.925, -76.65,
-76.321, -75.997, -75.958, -76.006])]
yp0list = [np.array([34.2]),
np.array([34.2, 34.5]),
np.array([34.2, 34.5, 34.8]),
np.array([34.2, 34.5, 34.8]),
np.array([35.1, 35.2]),
np.array([-52.068, -51.377, -50.729, -49.845, -49.192, -48.507,
-47.875, -47.478, -47.08, -46.422])]
yp1list = [np.array([34.5]),
np.array([34.5, 34.8]),
np.array([34.5, 34.8, 35.1]),
np.array([34.5, 34.8, 34.6]),
np.array([35.2, 35.4]),
np.array([-51.377, -50.729, -49.845, -49.192, -48.507, -47.875,
-47.478, -47.08, -46.422, -45.659])]
for i in range(0, len(xp0list)):
xp0 = xp0list[i]
xp1 = xp1list[i]
yp0 = yp0list[i]
yp1 = yp1list[i]
name = names[i]
mean_value = means[i]
std_value = stds[i]
zp = np.zeros(xp0.shape)
strike = azimuth(xp0[0], yp0[0], xp1[-1], yp1[-1])
widths = np.ones(xp0.shape) * WIDTH
dips = np.ones(xp0.shape) * DIP
strike = [strike]
origin = Origin({'eventsourcecode': 'test', 'lat': 0, 'lon': 0,
'depth': 5.0, 'mag': 7.0})
rupture = QuadRupture.fromTrace(
xp0, yp0, xp1, yp1, zp, widths, dips, origin, strike=strike)
# make a grid of points over both quads, ask for depths
ymin = np.nanmin(rupture.lats)
ymax = np.nanmax(rupture.lats)
xmin = np.nanmin(rupture.lons)
xmax = np.nanmax(rupture.lons)
xmin = np.floor(xmin * (1 / GRIDRES)) / (1 / GRIDRES)
xmax = np.ceil(xmax * (1 / GRIDRES)) / (1 / GRIDRES)
ymin = np.floor(ymin * (1 / GRIDRES)) / (1 / GRIDRES)
ymax = np.ceil(ymax * (1 / GRIDRES)) / (1 / GRIDRES)
geodict = GeoDict.createDictFromBox(
xmin, xmax, ymin, ymax, GRIDRES, GRIDRES)
nx = geodict.nx
ny = geodict.ny
depths = np.zeros((ny, nx))
for row in range(0, ny):
for col in range(0, nx):
lat, lon = geodict.getLatLon(row, col)
depth = rupture.getDepthAtPoint(lat, lon)
depths[row, col] = depth
np.testing.assert_almost_equal(np.nanmean(depths), mean_value)
np.testing.assert_almost_equal(np.nanstd(depths), std_value)
if interactive:
fig, axes = plt.subplots(nrows=2, ncols=1)
ax1, ax2 = axes
xdata = np.append(xp0, xp1[-1])
ydata = np.append(yp0, yp1[-1])
plt.sca(ax1)
plt.plot(xdata, ydata, 'b')
plt.sca(ax2)
im = plt.imshow(depths, cmap='viridis_r') # noqa
ch = plt.colorbar() # noqa
fname = os.path.join(os.path.expanduser('~'),
'quad_%s_test.png' % name)
print('Saving image for %s quad test... %s' % (name, fname))
plt.savefig(fname)
plt.close()
