def test_ss3_m4p5():
magnitude = 4.5
dip = np.array([90])
rake = 180.0
width = np.array([15])
fltx = np.array([0, 0])
flty = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * flty[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = rupture.QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='ss3')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'id': 'ss3',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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_so6():
event_name = 'so6'
magnitude = 7.2
dip = np.array([70])
rake = 135
width = np.array([15])
L = 80
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse = True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference = 'rv4')
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)
tmp = flt.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)
event = {'lat': epilat,
'lon': epilon,
'depth':epidepth,
'mag': magnitude,
'id':'so6',
'locstring':'so6',
'type':'RV',
'timezone':'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
fltlat = [a.latitude for a in flt.getQuadrilaterals()[0]]
fltlon = [a.longitude for a in flt.getQuadrilaterals()[0]]
fltlat = np.append(fltlat, fltlat[0])
fltlon = np.append(fltlon, fltlon[0])
fltx,flty = proj(fltlon, fltlat, reverse = False)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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_rv4():
magnitude = 7.0
rake = 90.0
width = np.array([28])
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='')
L = flt.getFaultLength()
# Try to figure out epicenter
tmp = flt.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)
event = {'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'id': 'test',
'locstring': 'rv4',
'type': 'DS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
fltx = np.array([0, 0])
flty = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * flty[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='ss3')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'id': 'ss3',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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])
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='')
L = flt.getFaultLength()
# Try to figure out epicenter
tmp = flt.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)
event = {'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'id': 'test',
'locstring': 'rv4',
'type': 'DS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, slat, slon, deps, T=2.0)
# Test fd
fd = test1.getFd()
fd_test = np.array(
[[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.72147747e-03, 1.34981119e-03, 8.95673480e-29,
1.24449087e-03, 1.16145147e-03, 2.25470229e-03,
7.05301515e-04, 0.00000000e+00],
[ 0.00000000e+00, 0.00000000e+00, 7.62625126e-03,
1.25136528e-02, 5.61909403e-03, 3.18694606e-28,
4.52275052e-03, 4.67980272e-03, 1.02822365e-02,
5.13171639e-03, -6.13935060e-03],
[ 0.00000000e+00, 4.00499692e-03, 2.37611880e-02,
2.37143264e-02, 9.55241972e-03, 5.65693221e-28,
7.70357238e-03, 7.36477919e-03, 1.48241947e-02,
8.40402367e-03, -1.58594139e-02],
[ 8.08392720e-19, 9.38156493e-03, 3.38613859e-02,
3.85355818e-02, 1.91047521e-02, 1.27066310e-27,
1.54323543e-02, 1.21915074e-02, 2.04437211e-02,
1.04933053e-02, -1.85937074e-02],
[ 2.12026318e-18, 1.37316424e-02, 4.40195705e-02,
6.16565712e-02, 4.77616016e-02, 5.07336347e-27,
3.86325509e-02, 1.97966900e-02, 2.64883302e-02,
1.23336661e-02, -2.07390404e-02],
[ 2.64338576e-18, 1.45898071e-02, 4.89104103e-02,
7.70703129e-02, 9.55225254e-02, 1.01875104e-01,
7.73459333e-02, 2.50275520e-02, 2.93537605e-02,
1.30949772e-02, -2.15685118e-02],
[ 2.64330042e-18, 1.45898071e-02, 4.89104103e-02,
7.70703129e-02, 9.55225254e-02, 1.01910945e-01,
7.74050830e-02, 2.52307951e-02, 2.92970785e-02,
1.30880672e-02, -2.15685118e-02],
[ 2.64318867e-18, 1.45898071e-02, 4.89104103e-02,
7.70703129e-02, 9.55225254e-02, 1.01933432e-01,
7.74421253e-02, 2.53572928e-02, 2.92615177e-02,
1.30837449e-02, -2.15685118e-02],
[ 2.64305117e-18, 1.45898071e-02, 4.89104103e-02,
7.70703129e-02, 9.55225254e-02, 1.01942593e-01,
7.74571361e-02, 2.54081650e-02, 2.92472178e-02,
1.30820173e-02, -2.15685118e-02],
[ 2.30140686e-18, 1.40209885e-02, 4.56202616e-02,
6.63103459e-02, 5.79255225e-02, 7.72925496e-27,
4.69663059e-02, 2.18399567e-02, 2.72863359e-02,
1.25728195e-02, -2.10226512e-02],
[ 1.10671369e-18, 1.04775558e-02, 3.59035524e-02,
4.24605614e-02, 2.24210618e-02, 1.53459722e-27,
1.81723013e-02, 1.39298662e-02, 2.14953705e-02,
1.08710398e-02, -1.90800441e-02]]
)
np.testing.assert_allclose(fd, fd_test, rtol=1e-5)
def test_so6():
event_name = 'so6'
magnitude = 7.2
dip = np.array([70])
rake = 135
width = np.array([15])
L = 80
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
reference='rv4')
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)
tmp = flt.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)
event = {
'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'id': 'so6',
'locstring': 'so6',
'type': 'RV',
'timezone': 'UTC'
}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
fltlat = [a.latitude for a in flt.getQuadrilaterals()[0]]
fltlon = [a.longitude for a in flt.getQuadrilaterals()[0]]
fltlat = np.append(fltlat, fltlat[0])
fltlon = np.append(fltlon, fltlon[0])
fltx, flty = proj(fltlon, fltlat, reverse=False)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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_rv4():
magnitude = 7.0
rake = 90.0
width = np.array([28])
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
reference='')
L = flt.getFaultLength()
# Try to figure out epicenter
tmp = flt.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)
event = {
'lat': epilat,
'lon': epilon,
'depth': epidepth,
'mag': magnitude,
'id': 'test',
'locstring': 'rv4',
'type': 'DS',
'timezone': 'UTC'
}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
fltx = np.array([0, 0])
flty = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * flty[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = fault.Fault.fromTrace(np.array([tlon[0]]),
np.array([tlat[0]]),
np.array([tlon[1]]),
np.array([tlat[1]]),
zp,
width,
dip,
reference='ss3')
event = {
'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'id': 'ss3',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'
}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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_ss3_move_hypo1():
magnitude = 7.2
dip = np.array([90])
rake = 180.0
width = np.array([15])
fltx = np.array([0, 0])
flty = 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(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = rupture.QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='ss3')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': -1.0,
'mag': magnitude,
'id': 'ss3',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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.])
fltx = np.array([0., 0., 10., 20.])
flty = 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(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = rupture.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, reference='')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': 1.0,
'mag': magnitude,
'id': '',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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_m6():
magnitude = 6.0
dip = np.array([90])
rake = 180.0
width = np.array([15])
fltx = np.array([0, 0])
flty = np.array([0, 80])
zp = np.array([0])
epix = np.array([0])
epiy = np.array([0.2 * flty[1]])
# Convert to lat/lon
proj = geo.utils.get_orthographic_projection(-122, -120, 39, 37)
tlon, tlat = proj(fltx, flty, reverse=True)
epilon, epilat = proj(epix, epiy, reverse=True)
flt = rupture.QuadRupture.fromTrace(
np.array([tlon[0]]), np.array([tlat[0]]),
np.array([tlon[1]]), np.array([tlat[1]]),
zp, width, dip, reference='ss3')
event = {'lat': epilat[0],
'lon': epilon[0],
'depth': 10,
'mag': magnitude,
'id': 'ss3',
'locstring': 'test',
'type': 'SS',
'timezone': 'UTC'}
event['time'] = ShakeDateTime.utcfromtimestamp(int(time.time()))
event['created'] = ShakeDateTime.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)
source = Source(event, flt)
source.setEventParam('rake', rake)
test1 = Bayless2013(source, 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)
