def _test(vs30file=None):
print('Testing creation of Sites object with Vs30 file of %s...' % vs30file)
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 3.0
yspan = 3.0
mysite = Sites.createFromCenter(cx,cy,xspan,yspan,dx,dy,vs30File=vs30file,
padding=True,resample=False)
sc = mysite.getSitesContext()
cx = -118.2
cy = 83
dx = 0.0083
dy = 0.0083
xspan = 3.0
yspan = 3.0
mysite = Sites.createFromCenter(cx,cy,xspan,yspan,dx,dy,vs30File=vs30file,padding=True,resample=False)
xmin = 116.234
xmax = 120.876
ymin = 20.12345
ymax = 24.75435
dx = 0.0083
dy = 0.0083
mysite = Sites.createFromBounds(xmin,xmax,ymin,ymax,dx,dy,vs30File=vs30file,padding=False,resample=False)
print('Passed creation of Sites object with Vs30 file of %s' % vs30file)
def _test(vs30file=None):
print('Testing creation of Sites object with Vs30 file of %s...' %
vs30file)
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 3.0
yspan = 3.0
mysite = Sites.createFromCenter(cx,
cy,
xspan,
yspan,
dx,
dy,
vs30File=vs30file,
padding=True,
resample=False)
sc = mysite.getSitesContext()
cx = -118.2
cy = 83
dx = 0.0083
dy = 0.0083
xspan = 3.0
yspan = 3.0
mysite = Sites.createFromCenter(cx,
cy,
xspan,
yspan,
dx,
dy,
vs30File=vs30file,
padding=True,
resample=False)
xmin = 116.234
xmax = 120.876
ymin = 20.12345
ymax = 24.75435
dx = 0.0083
dy = 0.0083
mysite = Sites.createFromBounds(xmin,
xmax,
ymin,
ymax,
dx,
dy,
vs30File=vs30file,
padding=False,
resample=False)
print('Passed creation of Sites object with Vs30 file of %s' % vs30file)
def set_sites_depth_parameters(sites, gmpe):
"""
Need to select the appropriate z1pt0 value for different GMPEs.
Note that these are required site parameters, so even though
OQ has these equations built into the class in most cases.
I have submitted an issue to OQ requesting subclasses of these
methods that do not require the depth parameters in the
SitesContext to make this easier.
:param sites:
A sites context.
:param gmpe:
A GMPE instance.
:returns:
A sites context with the depth parameters set for the
requested GMPE.
"""
sites = Sites._addDepthParameters(sites)
if gmpe == 'AbrahamsonEtAl2014()':
sites.z1pt0 = sites.z1pt0_ask14_cal
if gmpe == 'ChiouYoungs2014()':
# Also BooreEtAl2014() if using subclass with depth parameter
sites.z1pt0 = sites.z1pt0_cy14_cal
if gmpe == 'CampbellBozorgnia2014()':
sites.z2pt5 = sites.z2pt5_cb14_cal
if gmpe == 'ChiouYoungs2008()':
sites.z1pt0 = sites.z1pt0_cy08
if gmpe == 'CampbellBozorgnia2008()':
sites.z2pt5 = sites.z2pt5_cb07
return sites
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, "id": ""})
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_exceptions():
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
# Make souce instance
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.])
# Rupture requires an origin even when not used:
origin = Origin({'id':'test','lat':0,'lon':0,'depth':5.0,'mag':7.0})
rup = QuadRupture.fromTrace(lon0, lat0, lon1, lat1, z, W, dip,
origin)
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'type': 'U', 'mech':'RS',
'rake':90, 'timezone': 'UTC'}
origin = Origin(event)
gmpelist = ["Primate"]
with pytest.raises(Exception) as e:
dists = Distance.fromSites(gmpelist, origin, site, rup)
gmpelist = [AbrahamsonEtAl2014()]
sctx = site.getSitesContext()
dist_types = ['repi', 'rhypo', 'rjb', 'rrup', 'rx', 'ry', 'ry0', 'U', 'V']
with pytest.raises(Exception) as e:
dists = get_distance(dist_types, sctx.lats, sctx.lons,
np.zeros_like(sctx.lons), rup)
dist_types = ['repi', 'rhypo', 'rjb', 'rrup', 'rx', 'ry', 'ry0', 'U', 'T']
with pytest.raises(Exception) as e:
dists = get_distance(dist_types, sctx.lats, sctx.lons[0:4,],
np.zeros_like(sctx.lons), rup)
def test_exceptions():
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
# Make souce instance
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.])
flt = Fault.fromTrace(lon0, lat0, lon1, lat1, z, W, dip)
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'type': 'U', 'mech':'RS',
'rake':90,
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone': 'UTC'}
source = Source(event, flt)
gmpelist = ["Primate"]
with pytest.raises(Exception) as e:
dists = Distance.fromSites(gmpelist, source, site)
gmpelist = [AbrahamsonEtAl2014()]
sctx = site.getSitesContext()
dist_types = ['repi', 'rhypo', 'rjb', 'rrup', 'rx', 'ry', 'ry0', 'U', 'V']
with pytest.raises(Exception) as e:
dists = get_distance(dist_types, sctx.lats, sctx.lons,
np.zeros_like(sctx.lons), source)
dist_types = ['repi', 'rhypo', 'rjb', 'rrup', 'rx', 'ry', 'ry0', 'U', 'T']
with pytest.raises(Exception) as e:
dists = get_distance(dist_types, sctx.lats, sctx.lons[0:4,],
np.zeros_like(sctx.lons), source)
def test(vs30file=None):
vs30file = os.path.join(shakedir, 'data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
mysite = Sites.createFromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file, padding=True,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array(
[[ 409.14199829, 428.24468994, 395.90026855, 426.31658936,
427.53845215, 433.40481567, 436.59918213, 440.43664551,
413.60662842],
[ 423.60855103, 426.64892578, 398.89712524, 428.88549805,
428.78335571, 428.58578491, 430.54354858, 433.59750366,
415.18811035],
[ 391.67398071, 426.20635986, 425.57946777, 428.21954346,
426.06726074, 421.86233521, 423.53192139, 426.25296021,
365.48190308],
[ 385.00396729, 428.14602661, 430.05944824, 429.3427124 ,
426.13626099, 409.76391602, 383.07299805, 372.39117432,
426.48486328],
[ 356.68756104, 432.64077759, 434.55209351, 432.21600342,
395.53771973, 419.31866455, 421.67749023, 426.23449707,
427.32818604],
[ 337.0546875 , 345.14605713, 403.78097534, 385.49118042,
413.04779053, 428.22869873, 427.00268555, 426.8951416 ,
425.62023926],
[ 403.78884888, 336.48217773, 347.82220459, 425.96798706,
432.0640564 , 429.40097046, 427.74179077, 427.00006104,
419.5062561 ],
[ 420.07458496, 330.57504272, 392.33255005, 430.33862305,
432.01391602, 429.43969727, 427.30435181, 425.96151733,
426.15856934]])
np.testing.assert_allclose(grd, grd_target)
sc = mysite.getSitesContext()
scsamp = mysite.sampleFromSites(np.array([34.1, 34.111]),
np.array([-118.2, -118.222]))
xmin = -118.2
xmax = -118.12
ymin = 34.05
ymax = 34.1
dx = 0.0083
dy = 0.0083
mysite = Sites.createFromBounds(xmin, xmax, ymin, ymax, dx, dy,
vs30File=vs30file, padding=False,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array(
[[ 426.13626099, 409.76391602, 383.07299805, 372.39117432,
426.48486328, 422.45065308, 417.21685791, 410.43737793,
405.33862305, 400.5239563 , 396.03030396],
[ 395.53771973, 419.31866455, 421.67749023, 426.23449707,
427.32818604, 424.84860229, 415.17590332, 407.5760498 ,
404.54788208, 402.28500366, 398.95913696],
[ 413.04779053, 428.22869873, 427.00268555, 426.8951416 ,
425.62023926, 419.60952759, 411.7961731 , 407.53509521,
406.22122192, 405.31622314, 402.92575073],
[ 432.0640564 , 429.40097046, 427.74179077, 427.00006104,
419.5062561 , 411.10830688, 407.48901367, 406.53305054,
406.59658813, 406.24887085, 406.17044067],
[ 432.01391602, 429.43969727, 427.30435181, 425.96151733,
426.15856934, 427.56121826, 397.67102051, 399.21054077,
404.54968262, 407.18515015, 410.00823975],
[ 426.76913452, 428.86270142, 425.99606323, 423.5692749 ,
423.59835815, 425.92758179, 408.44885254, 406.55810547,
409.06945801, 413.75210571, 417.71130371],
[ 423.1892395 , 427.91104126, 424.53796387, 419.47485352,
418.177948 , 424.14065552, 428.57913208, 432.95300293,
427.77731323, 431.46524048, 442.75540161],
[ 410.56729126, 423.15557861, 424.48355103, 419.27658081,
418.60211182, 423.86721802, 428.06176758, 432.42089844,
438.54446411, 448.37237549, 462.25509644],
[ 405.86877441, 414.27923584, 419.53878784, 396.18017578,
414.54452515, 419.80047607, 425.19824219, 424.48919678,
424.72061157, 431.52270508, 432.84347534]])
np.testing.assert_allclose(grd, grd_target)
def test_virtualipe():
#
# Set up the GMPE, IPE, and GMICE
#
gmpe_cy14 = ChiouYoungs2014()
gmpe = MultiGMPE.from_list([gmpe_cy14], [1.0])
gmice = WGRW12()
ipe = VirtualIPE.fromFuncs(gmpe, gmice)
#
# Use the Calexico event info
#
homedir = os.path.dirname(os.path.abspath(__file__))
datadir = os.path.abspath(os.path.join(homedir, '..', 'data',
'eventdata', 'Calexico', 'input'))
#
# Read the event, origin, and rupture files and produce Rupture and Origin
# objects
#
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
eventfile = os.path.join(datadir, 'event.xml')
rupturefile = os.path.join(datadir, 'wei_fault.txt')
origin_obj = Origin.fromFile(eventfile)
rupture_obj = read_rupture_file(origin_obj, rupturefile)
rx = rupture_obj.getRuptureContext([gmpe])
rx.rake = 45.
smdx = 0.0083333333
smdy = 0.0083333333
lonspan = 6.0
latspan = 4.0
vs30filename = os.path.join(datadir, '..', 'vs30', 'vs30.grd')
sites_obj_grid = Sites.fromCenter(
rx.hypo_lon, rx.hypo_lat, lonspan, latspan,
smdx, smdy, defaultVs30=760.0, vs30File=vs30filename,
vs30measured_grid=None, padding=False, resample=False
)
npts = 200
lats = np.empty(npts)
lons = np.empty(npts)
depths = np.zeros(npts)
for i in range(npts):
lats[i] = rx.hypo_lat
lons[i] = rx.hypo_lon + i * 0.01
lldict = {'lats': lats, 'lons': lons}
sx = sites_obj_grid.getSitesContext(lldict=lldict, rock_vs30=760.0)
dobj = Distance(gmpe, lons, lats, depths, rupture_obj)
dx = dobj.getDistanceContext()
sd_types = [oqconst.StdDev.TOTAL]
mmi_const_vs30, mmi_sd_const_vs30 = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
# These prints are just so a human can examine the outputs
# print(mmi_const_vs30)
# print(mmi_sd_const_vs30)
sx = sites_obj_grid.getSitesContext(lldict=lldict)
mmi_variable_vs30, mmi_sd_variable_vs30 = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
# print(mmi_variable_vs30)
# print(mmi_sd_variable_vs30)
sd_types = [oqconst.StdDev.TOTAL, oqconst.StdDev.INTRA_EVENT,
oqconst.StdDev.INTER_EVENT]
mmi_variable_vs30_intra, mmi_sd_variable_vs30_intra = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
# print(mmi_variable_vs30_intra)
# print(mmi_sd_variable_vs30_intra)
# assert(0) # Assert causes test to fail and prints to be displayed
#
# Try with PGA
#
gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(PGV)
gmpe.ALL_GMPES_HAVE_PGV = False
ipe = VirtualIPE.fromFuncs(gmpe, gmice)
mmi_pga, mmi_sd_pga = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
#
# Try with SA(1.0)
#
gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(PGA)
ipe = VirtualIPE.fromFuncs(gmpe, gmice)
mmi_psa, mmi_sd_psa = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
#
# This should raise an exception because the IMT isn't MMI
#
with pytest.raises(ValueError) as e:
mmi_psa, mmi_sd_psa = \
ipe.get_mean_and_stddevs(sx, rx, dx, PGA(), sd_types)
#
# This should raise an exception because no valid IMTs are available
#
gmpe.DEFINED_FOR_INTENSITY_MEASURE_TYPES.remove(SA)
with pytest.raises(ShakeMapException) as e:
ipe = VirtualIPE.fromFuncs(gmpe, gmice)
#
# Now do a GMPE that uses Rjb instead of Rrup
#
gmpe_ba14 = BooreEtAl2014()
gmpe = MultiGMPE.from_list([gmpe_ba14], [1.0])
ipe = VirtualIPE.fromFuncs(gmpe, gmice)
rx = rupture_obj.getRuptureContext([gmpe])
rx.rake = 45.
dobj = Distance(gmpe, lons, lats, depths, rupture_obj)
dx = dobj.getDistanceContext()
mmi_rjb, mmi_sd_rjb = \
ipe.get_mean_and_stddevs(sx, rx, dx, MMI(), sd_types)
#
# Test the results against a known standard
#
savefile = os.path.abspath(os.path.join(homedir, '..', 'data',
'eventdata', 'Calexico', 'virtualipe_test', 'savefile.npz'))
#
# If things change, set remake_save to True, and it will rebuild the
# saved data file against which the comparisons are done
# Remember to set this back to False once you've remade the test datafile
#
remake_save = False
if remake_save:
np.savez_compressed(savefile,
mmi_const_vs30 = mmi_const_vs30,
mmi_sd_const_vs30 = mmi_sd_const_vs30[0],
mmi_variable_vs30 = mmi_variable_vs30,
mmi_sd_variable_vs30 = mmi_sd_variable_vs30[0],
mmi_variable_vs30_intra = mmi_variable_vs30_intra,
mmi_sd_variable_vs30_total = mmi_sd_variable_vs30_intra[0],
mmi_sd_variable_vs30_intra = mmi_sd_variable_vs30_intra[1],
mmi_sd_variable_vs30_inter = mmi_sd_variable_vs30_intra[2],
mmi_pga = mmi_pga,
mmi_sd_pga = mmi_sd_pga[0],
mmi_psa = mmi_psa,
mmi_sd_psa = mmi_sd_psa[0],
mmi_rjb = mmi_rjb,
mmi_sd_rjb = mmi_sd_rjb[0])
td = np.load(savefile)
assert(np.allclose(td['mmi_const_vs30'], mmi_const_vs30))
assert(np.allclose(td['mmi_sd_const_vs30'], mmi_sd_const_vs30[0]))
assert(np.allclose(td['mmi_variable_vs30'], mmi_variable_vs30))
assert(np.allclose(td['mmi_sd_variable_vs30'], mmi_sd_variable_vs30[0]))
assert(np.allclose(td['mmi_variable_vs30_intra'], mmi_variable_vs30_intra))
assert(np.allclose(td['mmi_sd_variable_vs30_total'],
mmi_sd_variable_vs30_intra[0]))
assert(np.allclose(td['mmi_sd_variable_vs30_intra'],
mmi_sd_variable_vs30_intra[1]))
assert(np.allclose(td['mmi_sd_variable_vs30_inter'],
mmi_sd_variable_vs30_intra[2]))
assert(np.allclose(td['mmi_pga'], mmi_pga))
assert(np.allclose(td['mmi_sd_pga'], mmi_sd_pga[0]))
assert(np.allclose(td['mmi_psa'], mmi_psa))
assert(np.allclose(td['mmi_sd_psa'], mmi_sd_psa[0]))
assert(np.allclose(td['mmi_rjb'], mmi_rjb))
assert(np.allclose(td['mmi_sd_rjb'], mmi_sd_rjb[0]))
# The total uncertainties should be greater than the intra-event
assert(np.all(mmi_sd_variable_vs30[0] > mmi_sd_variable_vs30_intra[1]))
# The combined intra and inter-event uncertainty should be equal
# to the total
tot = np.sqrt(mmi_sd_variable_vs30_intra[1]**2 + mmi_sd_variable_vs30_intra[2]**2)
assert(np.allclose(tot, mmi_sd_variable_vs30_intra[0], rtol=1e-2))
def test_sites(vs30file=None):
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
mysite = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file, padding=True,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array([[ 426.64892578, 398.89712524, 428.88549805, 428.78335571,
428.58578491, 430.54354858, 433.59750366],
[ 426.20635986, 425.57946777, 428.21954346, 426.06726074,
421.86233521, 423.53192139, 426.25296021],
[ 428.14602661, 430.05944824, 429.3427124 , 426.13626099,
409.76391602, 383.07299805, 372.39117432],
[ 432.64077759, 434.55209351, 432.21600342, 395.53771973,
419.31866455, 421.67749023, 426.23449707],
[ 345.14605713, 403.78097534, 385.49118042, 413.04779053,
428.22869873, 427.00268555, 426.8951416 ],
[ 336.48217773, 347.82220459, 425.96798706, 432.0640564 ,
429.40097046, 427.74179077, 427.00006104],
[ 330.57504272, 392.33255005, 430.33862305, 432.01391602,
429.43969727, 427.30435181, 425.96151733]])
np.testing.assert_allclose(grd, grd_target)
sc = mysite.getSitesContext()
scr = mysite.getSitesContext(rock_vs30 = 760.0)
grd = sc.backarc
grdt = np.array([[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False]], dtype=bool)
np.testing.assert_allclose(grd, grdt)
grd = sc.lats
grdt = np.array([ 34.075 , 34.08333333, 34.09166667, 34.1 ,
34.10833333, 34.11666667, 34.125 ])
np.testing.assert_allclose(grd, grdt)
grd = sc.lons
grdt = np.array([-118.225 , -118.21666667, -118.20833333, -118.2 ,
-118.19166667, -118.18333333, -118.175 ])
np.testing.assert_allclose(grd, grdt)
grd = sc.vs30
grdt = np.array([[ 426.64892578, 398.89712524, 428.88549805, 428.78335571,
428.58578491, 430.54354858, 433.59750366],
[ 426.20635986, 425.57946777, 428.21954346, 426.06726074,
421.86233521, 423.53192139, 426.25296021],
[ 428.14602661, 430.05944824, 429.3427124 , 426.13626099,
409.76391602, 383.07299805, 372.39117432],
[ 432.64077759, 434.55209351, 432.21600342, 395.53771973,
419.31866455, 421.67749023, 426.23449707],
[ 345.14605713, 403.78097534, 385.49118042, 413.04779053,
428.22869873, 427.00268555, 426.8951416 ],
[ 336.48217773, 347.82220459, 425.96798706, 432.0640564 ,
429.40097046, 427.74179077, 427.00006104],
[ 330.57504272, 392.33255005, 430.33862305, 432.01391602,
429.43969727, 427.30435181, 425.96151733]])
np.testing.assert_allclose(grd, grdt)
grd = scr.vs30
grdt = np.array([[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.],
[ 760., 760., 760., 760., 760., 760., 760.]])
np.testing.assert_allclose(grd, grdt)
grd = sc.vs30measured
grdt = np.array([[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False],
[False, False, False, False, False, False, False]], dtype=bool)
np.testing.assert_allclose(grd, grdt)
grd = sc.z1pt0_ask14_cal
grdt = np.array([[ 335.06579012, 366.39725582, 332.4593083 , 332.57855835,
332.80916279, 330.52077553, 326.93706615],
[ 335.58036296, 336.30856215, 333.23643861, 335.74201097,
340.60915547, 338.68122322, 335.52619949],
[ 333.32217548, 331.08730312, 331.92526979, 335.66183031,
354.37798647, 383.19730994, 394.00166561],
[ 328.06152136, 325.81357093, 328.56025522, 370.03738338,
343.53423548, 340.82221914, 335.54765968],
[ 419.3225465 , 361.03999163, 380.68893324, 350.67806177,
333.2257608 , 334.65418562, 334.77934134],
[ 426.64586941, 416.9870982 , 335.85735317, 328.73858131,
331.85719411, 333.79341356, 334.65724021],
[ 431.42758271, 373.4746626 , 330.76064671, 328.79741743,
331.81193751, 334.30299304, 335.86486938]])
np.testing.assert_allclose(grd, grdt)
grd = sc.z1pt0_cy08
grdt = np.array([[ 183.2043947 , 217.27787758, 180.56690603, 180.68687904,
180.91907101, 178.625999 , 175.08452094],
[ 183.72884833, 184.47314285, 181.34994816, 183.89385557,
188.91901585, 186.91536614, 183.67358657],
[ 181.43651087, 179.19139187, 180.03044953, 183.81199342,
203.71493023, 237.03939223, 250.05192732],
[ 176.18920323, 173.98674225, 176.68107716, 221.49002942,
191.99154431, 189.14149784, 183.69548028],
[ 280.25774719, 211.16371072, 234.04298229, 199.65723106,
181.33916991, 182.78577761, 182.91298179],
[ 288.5669674 , 277.54780981, 184.01166928, 176.85723522,
179.96216197, 181.91290358, 182.78888133],
[ 293.80330679, 225.506479 , 178.86520526, 176.91538893,
179.91677656, 182.42922842, 184.01934871]])
np.testing.assert_allclose(grd, grdt)
grd = sc.z1pt0_cy14_cal
grdt = np.array([[ 322.09231215, 357.07647045, 319.22097485, 319.3522119 ,
319.60603217, 317.08933532, 313.15733537],
[ 322.65987959, 323.46347258, 320.07644714, 322.83822344,
328.21884905, 326.08502532, 322.60012698],
[ 320.17085962, 317.71195569, 318.63340828, 322.74975843,
343.55342441, 376.19315199, 388.62006436],
[ 314.38985785, 311.92697475, 314.93687894, 361.19727923,
331.46256533, 328.4548676 , 322.62380134],
[ 418.15243574, 351.03313981, 373.32295288, 339.41631214,
320.0646893 , 321.63848529, 321.7764637 ],
[ 426.80110483, 415.40447342, 322.96549285, 315.13252356,
318.55852723, 320.68989724, 321.64185267],
[ 432.47426567, 365.09924657, 317.35292206, 315.19707981,
318.50874868, 321.25138528, 322.9737867 ]])
np.testing.assert_allclose(grd, grdt)
grd = sc.z2pt5_cb07
grdt = np.array([[ 1177.61979893, 1300.11396989, 1168.13802718, 1168.56933015,
1169.4040603 , 1161.16046639, 1148.4288528 ],
[ 1179.50520975, 1182.18094855, 1170.95306363, 1180.09841078,
1198.16386197, 1190.96074128, 1179.30654372],
[ 1171.26425658, 1163.19305376, 1166.20946607, 1179.80411634,
1251.35517419, 1371.15661506, 1417.9366787 ],
[ 1152.40018562, 1144.48233838, 1154.16847239, 1315.25665576,
1209.20960179, 1198.96368474, 1179.3852516 ],
[ 1526.52660116, 1278.13354004, 1360.38452132, 1236.76774567,
1170.91431583, 1176.11487052, 1176.57216955],
[ 1556.3982478 , 1516.78437627, 1180.52195107, 1154.8017606 ,
1165.96397227, 1172.97688837, 1176.12602836],
[ 1575.22288791, 1329.69579201, 1162.02041292, 1155.01082322,
1165.80081172, 1174.83307617, 1180.5495586 ]])
np.testing.assert_allclose(grd, grdt)
grd = sc.z2pt5_cb14_cal
grdt = np.array([[ 1.17466154, 1.26861168, 1.1676564 , 1.16797461, 1.16859058,
1.16251358, 1.15315136],
[ 1.17605704, 1.17803908, 1.16973403, 1.17649629, 1.18992131,
1.18455663, 1.17590996],
[ 1.16996381, 1.16401074, 1.166234 , 1.17627836, 1.230198 ,
1.32873844, 1.37243028],
[ 1.15606906, 1.15025389, 1.15736893, 1.2809454 , 1.19818264,
1.19051805, 1.17596823],
[ 1.49705669, 1.25107322, 1.31920733, 1.21901552, 1.16970542,
1.1735483 , 1.17388652],
[ 1.54123541, 1.48388699, 1.17680997, 1.15783457, 1.16605299,
1.17122878, 1.17355655],
[ 1.57278236, 1.29292406, 1.1631469 , 1.1579883 , 1.16593269,
1.17260055, 1.17683042]])
np.testing.assert_allclose(grd, grdt)
lldict = {'lats':np.array([34.1, 34.111]),
'lons':np.array([-118.2, -118.222])}
scsamp = mysite.getSitesContext(lldict)
vs30 = scsamp.vs30
vs30t = np.array([ 395.53771973, 428.14602661])
np.testing.assert_allclose(vs30, vs30t)
lldict = {'lats':np.array([34.1, 34.111]),
'lons':np.array([-118.2, -118.222])}
scrsamp = mysite.getSitesContext(lldict, rock_vs30=760)
vs30 = scrsamp.vs30
vs30t = np.array([ 760., 760.])
np.testing.assert_allclose(vs30, vs30t)
lats = np.array([34.1, 34.111])
lons = np.array([-118.2, -118.222])
lldict = {'lats':lats, 'lons':lons}
scsamp = mysite.getSitesContext(lldict)
grd = scsamp.vs30measured
grdt = np.array([False, False], dtype=bool)
np.testing.assert_allclose(grd, grdt)
with pytest.raises(Exception) as e:
scsamp = mysite.getSitesContextFromLatLon(
np.array([34.1, 34.111, 34.5]),
np.array([-118.2, -118.222]))
mysite = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=None, padding=True,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array(
[[ 686., 686., 686., 686., 686., 686.],
[ 686., 686., 686., 686., 686., 686.],
[ 686., 686., 686., 686., 686., 686.],
[ 686., 686., 686., 686., 686., 686.],
[ 686., 686., 686., 686., 686., 686.],
[ 686., 686., 686., 686., 686., 686.]])
np.testing.assert_allclose(grd, grd_target)
xmin = -118.2
xmax = -118.12
ymin = 34.05
ymax = 34.1
dx = 0.0083
dy = 0.0083
mysite = Sites.fromBounds(xmin, xmax, ymin, ymax, dx, dy,
vs30File=vs30file, padding=False,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array([[ 395.53771973, 419.31866455, 421.67749023, 426.23449707,
427.32818604, 424.84860229, 415.17590332, 407.5760498 ,
404.54788208, 402.28500366],
[ 413.04779053, 428.22869873, 427.00268555, 426.8951416 ,
425.62023926, 419.60952759, 411.7961731 , 407.53509521,
406.22122192, 405.31622314],
[ 432.0640564 , 429.40097046, 427.74179077, 427.00006104,
419.5062561 , 411.10830688, 407.48901367, 406.53305054,
406.59658813, 406.24887085],
[ 432.01391602, 429.43969727, 427.30435181, 425.96151733,
426.15856934, 427.56121826, 397.67102051, 399.21054077,
404.54968262, 407.18515015],
[ 426.76913452, 428.86270142, 425.99606323, 423.5692749 ,
423.59835815, 425.92758179, 408.44885254, 406.55810547,
409.06945801, 413.75210571],
[ 423.1892395 , 427.91104126, 424.53796387, 419.47485352,
418.177948 , 424.14065552, 428.57913208, 432.95300293,
427.77731323, 431.46524048],
[ 410.56729126, 423.15557861, 424.48355103, 419.27658081,
418.60211182, 423.86721802, 428.06176758, 432.42089844,
438.54446411, 448.37237549]])
np.testing.assert_allclose(grd, grd_target)
mysite = Sites.fromBounds(xmin, xmax, ymin, ymax, dx, dy,
vs30File=None, padding=False,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array([[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.],
[ 686., 686., 686., 686., 686., 686., 686., 686., 686.,
686., 686.]])
np.testing.assert_allclose(grd, grd_target)
def test_multigmpe():
# Define gmpes and their weights
gmpes = [AbrahamsonEtAl2014(), BooreEtAl2014(),
CampbellBozorgnia2014(), ChiouYoungs2014()]
wts = [0.25, 0.25, 0.25, 0.25]
# Make sites instance
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.createFromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
sctx = site.getSitesContext()
sctx.vs30 = np.reshape(sctx.vs30, (-1,))
sctx.vs30measured = np.reshape(sctx.vs30measured, (-1,))
sctx.z1pt0 = np.reshape(sctx.z1pt0, (-1,))
# Need separate z1pt0 arrays
sctx.z1pt0cy14 = mg._z1_from_vs30_cy14_cal(sctx.vs30)
sctx.z1pt0ask14 = mg._z1_from_vs30_ask14_cal(sctx.vs30)
sctx.z2pt5 = mg._z2p5_from_vs30_cb14_cal(sctx.vs30) / 1000.0
# Make souce instance
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.])
flt = Fault.fromTrace(lon0, lat0, lon1, lat1, z, W, dip)
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'rake': 30.3,
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone': 'UTC'}
source = Source(event, flt)
# Make a rupture context
rupt = source.getRuptureContext(gmpes)
# Make a distance context
dctx = Distance.fromSites(gmpes, source, site).getDistanceContext()
dctx.rhypo = np.reshape(dctx.rhypo, (-1,))
dctx.rx = np.reshape(dctx.rx, (-1,))
dctx.rjb = np.reshape(dctx.rjb, (-1,))
dctx.ry0 = np.reshape(dctx.ry0, (-1,))
dctx.rrup = np.reshape(dctx.rrup, (-1,))
# Compute weighted GMPE
iimt = imt.PGV()
stddev_types = [const.StdDev.TOTAL]
mgmpe = mg.MultiGMPE.from_list(gmpes, wts)
lnmu, lnsd = mgmpe.get_mean_and_stddevs(
sctx, rupt, dctx, iimt, stddev_types)
lnmud = np.array(
[3.44828531, 3.49829605, 3.61749432, 3.64343805, 3.7001028,
3.7348924, 3.76927164, 3.78659955, 3.82600784, 3.46635007,
3.53816879, 3.6486898, 3.67058155, 3.72223342, 3.75403094,
3.79315031, 3.79871491, 3.82093027, 3.54889613, 3.57531437,
3.64441687, 3.69915981, 3.74491289, 3.78931599, 3.80957828,
3.80870754, 3.8731021, 3.5927326, 3.60764647, 3.66894024,
3.72148551, 3.75742965, 3.82164661, 3.86341308, 3.87171115,
3.79092594, 3.64153758, 3.61835381, 3.68166249, 3.7338161,
3.82454214, 3.81543928, 3.81507658, 3.80006803, 3.77165695,
3.65178742, 3.71324776, 3.70389969, 3.77034752, 3.78259432,
3.78677497, 3.79838465, 3.79050287, 3.75066018, 3.52883328,
3.67813977, 3.71754876, 3.65520574, 3.69463436, 3.72516445,
3.7457098, 3.74672185, 3.72615784, 3.44535551, 3.61907294,
3.58790363, 3.58068716, 3.61177983, 3.64349327, 3.66698468,
3.67129902, 3.65483002]
)
lnsdd = np.array(
[ 0.63560302, 0.63648101, 0.63610581, 0.6390135 , 0.64203528,
0.64624098, 0.64851812, 0.64640406, 0.64384305, 0.6361429 ,
0.63677975, 0.63715381, 0.64040366, 0.64404005, 0.64782624,
0.6476325 , 0.64509458, 0.64297808, 0.63477576, 0.63727968,
0.63899462, 0.64205578, 0.64604037, 0.64815296, 0.64609948,
0.64402734, 0.63844724, 0.6343891 , 0.63806041, 0.64043609,
0.64406094, 0.64776777, 0.64717195, 0.64297191, 0.64011346,
0.64110084, 0.63137566, 0.63864151, 0.64163093, 0.64588687,
0.64714873, 0.64603694, 0.64397734, 0.64217431, 0.63958323,
0.62883338, 0.63127469, 0.63961477, 0.64097303, 0.6442055 ,
0.64376449, 0.64273526, 0.64112115, 0.63815862, 0.63575399,
0.6291859 , 0.63180644, 0.6394421 , 0.63946545, 0.63947169,
0.63935499, 0.63832598, 0.63664816, 0.63595663, 0.62755689,
0.63523274, 0.63663489, 0.63631586, 0.63616589, 0.63597828,
0.63542126, 0.63500847])
np.testing.assert_allclose(lnmu, lnmud)
np.testing.assert_allclose(lnsd[0], lnsdd)
# Check for exception due to weights:
with pytest.raises(Exception) as a:
wts = [0.25, 0.25, 0.25, 0.25 + 1e-4]
mgmpe = mg.MultiGMPE.from_list(gmpes, wts)
# Check exception on GMPE check
with pytest.raises(Exception) as a:
wts = [1.0]
mgmpe = mg.MultiGMPE.from_list(['BA08'], wts)
# Check exception on tectonic region
with pytest.raises(Exception) as a:
gmpes = [BooreEtAl2014(), Campbell2003()]
wts = [0.5, 0.5]
mgmpe = mg.MultiGMPE.from_list(gmpes, wts)
# Check exception on length of gmpe and weight lenghts
with pytest.raises(Exception) as a:
gmpes = [BooreEtAl2014(), Campbell2003()]
wts = [1.0]
mgmpe = mg.MultiGMPE.from_list(gmpes, wts)
# Check PGV from a GMPE without PGV
gmpes = [Campbell2003()]
wts = [1.0]
mgmpe = mg.MultiGMPE.from_list(gmpes, wts)
lnmu, lnsd = mgmpe.get_mean_and_stddevs(
sctx, rupt, dctx, iimt, stddev_types)
lnmud = np.array(
[ 3.09152212, 3.1524312 , 3.20749883, 3.25431585, 3.29035521,
3.31326677, 3.32116911, 3.31341321, 3.29819842, 3.12252648,
3.18081138, 3.23208034, 3.27383205, 3.30358765, 3.319195 ,
3.31916753, 3.30623521, 3.28938984, 3.15235911, 3.20745205,
3.25429394, 3.29035582, 3.31328548, 3.32119931, 3.31344697,
3.2982328 , 3.27982759, 3.17945026, 3.23203088, 3.2738231 ,
3.30360265, 3.31922869, 3.31921198, 3.30628471, 3.28944133,
3.26955097, 3.18990634, 3.24351181, 3.28521502, 3.31195497,
3.32124956, 3.3135073 , 3.29830033, 3.27989827, 3.25860053,
3.17942778, 3.23201703, 3.27282524, 3.29888607, 3.3078892 ,
3.30156745, 3.2884687 , 3.26964276, 3.24701758, 3.14910673,
3.19888101, 3.23727522, 3.26163304, 3.2701699 , 3.2690822 ,
3.26201491, 3.24919602, 3.23101321, 3.10184816, 3.1475792 ,
3.18259748, 3.20467529, 3.21444387, 3.21832088, 3.21671138,
3.20966263, 3.19737325]
)
lnsdd = np.array(
[ 0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518, 0.83458518, 0.83458518, 0.83458518,
0.83458518, 0.83458518]
)
np.testing.assert_allclose(lnmu, lnmud)
np.testing.assert_allclose(lnsd[0], lnsdd)
def test_distance_from_sites_origin():
# Make sites instance
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
# Make souce instance
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.])
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'type': 'ALL',
'timezone': 'UTC'}
origin = Origin(event)
rup = QuadRupture.fromTrace(lon0, lat0, lon1, lat1, z, W, dip, origin)
gmpelist = [AbrahamsonEtAl2014(), BergeThierryEtAl2003SIGMA()]
dists = Distance.fromSites(gmpelist, site, rup)
dctx = dists.getDistanceContext()
rhypo = np.array([[ 3.74498133, 3.32896405, 3.05225679, 2.95426722, 3.05225679,
3.32896405, 3.74498133],
[ 3.11965436, 2.60558436, 2.24124201, 2.10583262, 2.24124201,
2.60558436, 3.11965436],
[ 2.67523213, 2.05265767, 1.564393 , 1.36331682, 1.564393 ,
2.05265767, 2.67523213],
[ 2.50973226, 1.83166664, 1.26045653, 1. , 1.26045653,
1.83166664, 2.50973226],
[ 2.67542717, 2.05277065, 1.56443006, 1.36331682, 1.56443006,
2.05277065, 2.67542717],
[ 3.11998886, 2.60576236, 2.24129374, 2.10583262, 2.24129374,
2.60576236, 3.11998886],
[ 3.74539929, 3.32917303, 3.05231378, 2.95426722, 3.05231378,
3.32917303, 3.74539929]])
np.testing.assert_allclose(
rhypo, dctx.rhypo, rtol=0, atol=0.01)
rx = np.array([[ -3.18894050e+00, -2.48001769e+00, -1.77111874e+00,
-1.06224366e+00, -3.53392480e-01, 3.55434794e-01,
1.06423815e+00],
[ -2.83506890e+00, -2.12607622e+00, -1.41710740e+00,
-7.08162466e-01, 7.58576362e-04, 7.09655709e-01,
1.41852892e+00],
[ -2.48119723e+00, -1.77213470e+00, -1.06309603e+00,
-3.54081243e-01, 3.54909645e-01, 1.06387662e+00,
1.77281967e+00],
[ -2.12732550e+00, -1.41819312e+00, -7.09084619e-01,
2.56774082e-12, 7.09060719e-01, 1.41809752e+00,
2.12711040e+00],
[ -1.77345370e+00, -1.06425151e+00, -3.55073182e-01,
3.54081255e-01, 1.06321179e+00, 1.77231841e+00,
2.48140110e+00],
[ -1.41958186e+00, -7.10309855e-01, -1.06172493e-03,
7.08162516e-01, 1.41736285e+00, 2.12653927e+00,
2.83569175e+00],
[ -1.06570997e+00, -3.56368176e-01, 3.52949744e-01,
1.06224377e+00, 1.77151390e+00, 2.48076010e+00,
3.18998236e+00]])
np.testing.assert_allclose(
rx, dctx.rx, rtol=0, atol=0.01)
rjb = np.array([[ 3.19372137e+00, 2.48373511e+00, 1.77377308e+00,
1.06383562e+00, 3.53925643e-01, 2.25816823e-03,
2.45009861e-03],
[ 2.83931844e+00, 2.12926243e+00, 1.41923064e+00,
7.09223517e-01, 1.57594916e-03, 1.86044244e-03,
2.05239165e-03],
[ 2.48510934e+00, 1.77479025e+00, 1.06468863e+00,
3.54611655e-01, 1.04375185e-03, 1.32827303e-03,
1.52024106e-03],
[ 2.30690967e+00, 1.53793979e+00, 7.68969896e-01,
5.88918451e-12, 3.77111295e-04, 6.61660373e-04,
8.53647223e-04],
[ 2.48531877e+00, 1.79442084e+00, 1.20242597e+00,
8.54793253e-01, 5.62052963e-01, 2.69254693e-01,
5.26105100e-05],
[ 2.95646628e+00, 2.40489915e+00, 2.00231070e+00,
1.70958533e+00, 1.41681634e+00, 1.12398937e+00,
8.63761551e-01],
[ 3.60741953e+00, 3.17112489e+00, 2.85711592e+00,
2.56437623e+00, 2.27157856e+00, 1.97872291e+00,
1.78518260e+00]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
ry0 = np.array([[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[ 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[ 2.29490054e-02, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[ 8.79341006e-01, 5.86285236e-01, 2.93171565e-01,
6.21003581e-12, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[ 1.73573289e+00, 1.44264826e+00, 1.14950573e+00,
8.56305300e-01, 5.63046975e-01, 2.69730762e-01,
0.00000000e+00],
[ 2.59212463e+00, 2.29901116e+00, 2.00583977e+00,
1.71261048e+00, 1.41932329e+00, 1.12597821e+00,
8.32575235e-01],
[ 3.44851622e+00, 3.15537391e+00, 2.86217367e+00,
2.56891553e+00, 2.27559947e+00, 1.98222553e+00,
1.68879368e+00]])
np.testing.assert_allclose(
ry0, dctx.ry0, rtol=0, atol=0.01)
rrup = np.array([[ 3.34678672, 2.67788811, 2.03697073, 1.46129187, 1.06271102,
1.06352692, 1.40073832],
[ 3.01030105, 2.3526499 , 1.73673635, 1.22706347, 1.00157564,
1.22283363, 1.57764099],
[ 2.67858182, 2.03712377, 1.46095502, 1.06170931, 1.06220616,
1.39958479, 1.75442695],
[ 2.51415965, 1.8343632 , 1.26143652, 1. , 1.2212501 ,
1.57621925, 1.9310962 ],
[ 2.67877609, 2.05412785, 1.56384179, 1.3617346 , 1.50608502,
1.77308319, 2.10764873],
[ 3.12078859, 2.6043486 , 2.23799413, 2.09885629, 2.11696797,
2.23191013, 2.4299612 ],
[ 3.74318473, 3.32482368, 3.04635272, 2.9183523 , 2.86659485,
2.88815116, 2.98141559]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
def test_distance_no_rupture():
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'timezone': 'UTC'}
origin = Origin(event)
origin.setMechanism('ALL')
# Make sites instance
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.fromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
# Make souce instance
# - Unknown/no tectonic region
# - Mech is ALL
gmpe = AbrahamsonEtAl2014()
rupture = PointRupture(origin)
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.03475736, 0.82507289, 0.69891123, 0.6553167 , 0.69891123,
0.82507289, 1.03475736],
[ 0.72918893, 0.50725874, 0.36675284, 0.31957002, 0.36675284,
0.50725874, 0.72918893],
[ 0.53487557, 0.30135487, 0.14776055, 0.09290799, 0.14776055,
0.30135487, 0.53487557],
[ 0.46963915, 0.2280053 , 0.06643829, 0. , 0.06643829,
0.2280053 , 0.46963915],
[ 0.53495323, 0.30139344, 0.14777086, 0.09290799, 0.14777086,
0.30139344, 0.53495323],
[ 0.72933979, 0.50732902, 0.36677229, 0.31957002, 0.36677229,
0.50732902, 0.72933979],
[ 1.03497272, 0.82517579, 0.69893672, 0.6553167 , 0.69893672,
0.82517579, 1.03497272]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 8.26004043, 8.11921658, 8.11376473, 8.09579991, 8.11376473,
8.11921658, 8.26004043],
[ 8.12023764, 8.01816823, 7.93517669, 7.9600631 , 7.93517669,
8.01816823, 8.12023764],
[ 8.00702434, 7.95888951, 7.8881565 , 7.88352525, 7.8881565 ,
7.95888951, 8.00702434],
[ 8.02022568, 7.90722113, 7.85639147, 0. , 7.85639147,
7.90722113, 8.02022568],
[ 8.00698213, 7.95890141, 7.88813785, 7.88352525, 7.88813785,
7.95890141, 8.00698213],
[ 8.12025813, 8.01814988, 7.93520725, 7.9600631 , 7.93520725,
8.01814988, 8.12025813],
[ 8.26012423, 8.11931772, 8.1137722 , 8.09579991, 8.1137722 ,
8.11931772, 8.26012423]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region unsupported
# - Mech is ALL
origin._tectonic_region = 'Volcano'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjbt = np.array([[ 1.03475736, 0.82507289, 0.69891123, 0.6553167 , 0.69891123,
0.82507289, 1.03475736],
[ 0.72918893, 0.50725874, 0.36675284, 0.31957002, 0.36675284,
0.50725874, 0.72918893],
[ 0.53487557, 0.30135487, 0.14776055, 0.09290799, 0.14776055,
0.30135487, 0.53487557],
[ 0.46963915, 0.2280053 , 0.06643829, 0. , 0.06643829,
0.2280053 , 0.46963915],
[ 0.53495323, 0.30139344, 0.14777086, 0.09290799, 0.14777086,
0.30139344, 0.53495323],
[ 0.72933979, 0.50732902, 0.36677229, 0.31957002, 0.36677229,
0.50732902, 0.72933979],
[ 1.03497272, 0.82517579, 0.69893672, 0.6553167 , 0.69893672,
0.82517579, 1.03497272]])
np.testing.assert_allclose(
rjbt, dctx.rjb, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: active
# - Mech is ALL
origin.setMechanism('ALL')
origin._tectonic_region = 'Active Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.10115976, 0.88331216, 0.75077594, 0.70491937, 0.75077594,
0.88331216, 1.10115976],
[ 0.78261273, 0.54865189, 0.39914713, 0.34852149, 0.39914713,
0.54865189, 0.78261273],
[ 0.57800579, 0.32895654, 0.16294131, 0.10290794, 0.16294131,
0.32895654, 0.57800579],
[ 0.50865092, 0.25000954, 0.07371315, 0. , 0.07371315,
0.25000954, 0.50865092],
[ 0.57808833, 0.32899797, 0.16295256, 0.10290794, 0.16295256,
0.32899797, 0.57808833],
[ 0.78277133, 0.5487266 , 0.39916785, 0.34852149, 0.39916785,
0.5487266 , 0.78277133],
[ 1.10138329, 0.88341918, 0.75080275, 0.70491937, 0.75080275,
0.88341918, 1.10138329]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 8.72726953, 8.58534811, 8.58323541, 8.5654409 , 8.58323541,
8.58534811, 8.72726953],
[ 8.58922774, 8.4871601 , 8.40244887, 8.4297141 , 8.40244887,
8.4871601 , 8.58922774],
[ 8.47470803, 8.42880892, 8.35631312, 8.35201539, 8.35631312,
8.42880892, 8.47470803],
[ 8.49021276, 8.37536496, 8.32350188, 0. , 8.32350188,
8.37536496, 8.49021276],
[ 8.47466149, 8.42882081, 8.35629324, 8.35201539, 8.35629324,
8.42882081, 8.47466149],
[ 8.58924512, 8.48713903, 8.4024808 , 8.4297141 , 8.4024808 ,
8.48713903, 8.58924512],
[ 8.72735075, 8.58545174, 8.5832426 , 8.5654409 , 8.5832426 ,
8.58545174, 8.72735075]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: active
# - Mech is RS
origin.setMechanism('RS')
origin._tectonic_region = 'Active Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 0.94405696, 0.73298036, 0.61025288, 0.56806407, 0.61025288,
0.73298036, 0.94405696],
[ 0.63960501, 0.42680989, 0.29738908, 0.25562246, 0.29738908,
0.42680989, 0.63960501],
[ 0.45239173, 0.23958848, 0.10874248, 0.06508855, 0.10874248,
0.23958848, 0.45239173],
[ 0.39203111, 0.17571632, 0.04480241, 0. , 0.04480241,
0.17571632, 0.39203111],
[ 0.45246373, 0.2396224 , 0.1087508 , 0.06508855, 0.1087508 ,
0.2396224 , 0.45246373],
[ 0.63975135, 0.42687494, 0.29740691, 0.25562246, 0.29740691,
0.42687494, 0.63975135],
[ 0.94427453, 0.73308353, 0.61027758, 0.56806407, 0.61027758,
0.73308353, 0.94427453]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 8.81700098, 8.67259556, 8.6707467 , 8.65288076, 8.6707467 ,
8.67259556, 8.81700098],
[ 8.67672238, 8.57444747, 8.49014736, 8.5183922 , 8.49014736,
8.57444747, 8.67672238],
[ 8.56159881, 8.51774523, 8.44708824, 8.44391005, 8.44708824,
8.51774523, 8.56159881],
[ 8.57788943, 8.46484058, 8.41567031, 0. , 8.41567031,
8.46484058, 8.57788943],
[ 8.56155103, 8.51775668, 8.44706792, 8.44391005, 8.44706792,
8.51775668, 8.56155103],
[ 8.67673955, 8.5744255 , 8.49017946, 8.5183922 , 8.49017946,
8.5744255 , 8.67673955],
[ 8.81708413, 8.67270074, 8.67075389, 8.65288076, 8.67075389,
8.67270074, 8.81708413]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: active
# - Mech is NM
origin.setMechanism('NM')
origin._tectonic_region = 'Active Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 0.7899535 , 0.61128249, 0.50843465, 0.47310349, 0.50843465,
0.61128249, 0.7899535 ],
[ 0.53301769, 0.35495992, 0.24706995, 0.21231668, 0.24706995,
0.35495992, 0.53301769],
[ 0.37628889, 0.19897762, 0.09028387, 0.05409271, 0.09028387,
0.19897762, 0.37628889],
[ 0.32596438, 0.14586493, 0.03728933, 0. , 0.03728933,
0.14586493, 0.32596438],
[ 0.37634892, 0.19900584, 0.09029076, 0.05409271, 0.09029076,
0.19900584, 0.37634892],
[ 0.53314026, 0.35501415, 0.24708481, 0.21231668, 0.24708481,
0.35501415, 0.53314026],
[ 0.79013775, 0.61136979, 0.50845534, 0.47310349, 0.50845534,
0.61136979, 0.79013775]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 7.94857792, 7.8097532 , 7.80275055, 7.78489184, 7.80275055,
7.8097532 , 7.94857792],
[ 7.80938707, 7.70839546, 7.62713392, 7.65061937, 7.62713392,
7.70839546, 7.80938707],
[ 7.69799123, 7.64933048, 7.58013644, 7.57530397, 7.58013644,
7.64933048, 7.69799123],
[ 7.7099614 , 7.59905656, 7.54904995, 0. , 7.54904995,
7.59905656, 7.7099614 ],
[ 7.69795153, 7.64934225, 7.58011859, 7.57530397, 7.58011859,
7.64934225, 7.69795153],
[ 7.80940883, 7.70837861, 7.62716348, 7.65061937, 7.62716348,
7.70837861, 7.80940883],
[ 7.94866209, 7.80985208, 7.80275807, 7.78489184, 7.80275807,
7.80985208, 7.94866209]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: active
# - Mech is SS
origin.setMechanism('SS')
origin._tectonic_region = 'Active Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 2.00333625, 1.69987873, 1.49778447, 1.42682201, 1.49778447,
1.69987873, 2.00333625],
[ 1.54679373, 1.17582687, 0.914992 , 0.81812345, 0.914992 ,
1.17582687, 1.54679373],
[ 1.22626178, 0.78021345, 0.43426687, 0.29180829, 0.43426687,
0.78021345, 1.22626178],
[ 1.10672645, 0.62338097, 0.21787328, 0. , 0.21787328,
0.62338097, 1.10672645],
[ 1.22640328, 0.7802939 , 0.43429295, 0.29180829, 0.43429295,
0.7802939 , 1.22640328],
[ 1.54703738, 1.17595553, 0.9150287 , 0.81812345, 0.9150287 ,
1.17595553, 1.54703738],
[ 2.00364385, 1.7000298 , 1.49782584, 1.42682201, 1.49782584,
1.7000298 , 2.00364385]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 7.97494557, 7.79806013, 7.76281765, 7.735536 , 7.76281765,
7.79806013, 7.97494557],
[ 7.77614524, 7.62644695, 7.5120851 , 7.52225031, 7.5120851 ,
7.62644695, 7.77614524],
[ 7.62326525, 7.51608628, 7.40624352, 7.38577101, 7.40624352,
7.51608628, 7.62326525],
[ 7.61851685, 7.44728324, 7.35263272, 0. , 7.35263272,
7.44728324, 7.61851685],
[ 7.62324614, 7.51610811, 7.40622914, 7.38577101, 7.40622914,
7.51610811, 7.62324614],
[ 7.77620063, 7.62644821, 7.51211876, 7.52225031, 7.51211876,
7.62644821, 7.77620063],
[ 7.97507013, 7.798177 , 7.76283076, 7.735536 , 7.76283076,
7.798177 , 7.97507013]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: stable
# - Mech is all
origin.setMechanism('ALL')
origin._tectonic_region = 'Stable Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.25490086, 1.00456938, 0.85266727, 0.80013341, 0.85266727,
1.00456938, 1.25490086],
[ 0.8891456 , 0.621322 , 0.4507253 , 0.39310934, 0.4507253 ,
0.621322 , 0.8891456 ],
[ 0.65483395, 0.37085259, 0.18246645, 0.11472522, 0.18246645,
0.37085259, 0.65483395],
[ 0.57566287, 0.28111922, 0.08186392, 0. , 0.08186392,
0.28111922, 0.57566287],
[ 0.65492818, 0.37089972, 0.18247916, 0.11472522, 0.18247916,
0.37089972, 0.65492818],
[ 0.88932733, 0.62140729, 0.45074894, 0.39310934, 0.45074894,
0.62140729, 0.88932733],
[ 1.2551578 , 1.00469232, 0.85269799, 0.80013341, 0.85269799,
1.00469232, 1.2551578 ]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 6.37308879, 6.21401632, 6.17868645, 6.15460391, 6.17868645,
6.21401632, 6.37308879],
[ 6.19096821, 6.06108712, 5.96682577, 5.97487576, 5.96682577,
6.06108712, 6.19096821],
[ 6.05926472, 5.97000316, 5.88510619, 5.87109182, 5.88510619,
5.97000316, 6.05926472],
[ 6.05384337, 5.91573235, 5.84608701, 0. , 5.84608701,
5.91573235, 6.05384337],
[ 6.05925153, 5.97002045, 5.88509436, 5.87109182, 5.88509436,
5.97002045, 6.05925153],
[ 6.1910207 , 6.0610899 , 5.96685295, 5.97487576, 5.96685295,
6.0610899 , 6.1910207 ],
[ 6.37320723, 6.21411804, 6.17869829, 6.15460391, 6.17869829,
6.21411804, 6.37320723]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: stable
# - Mech is RS
origin.setMechanism('RS')
origin._tectonic_region = 'Stable Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.06775489, 0.83169032, 0.69344486, 0.645892 , 0.69344486,
0.83169032, 1.06775489],
[ 0.72652464, 0.48639585, 0.33959401, 0.2920419 , 0.33959401,
0.48639585, 0.72652464],
[ 0.51540522, 0.27378007, 0.12450057, 0.07451822, 0.12450057,
0.27378007, 0.51540522],
[ 0.44695345, 0.20099496, 0.05123817, 0. , 0.05123817,
0.20099496, 0.44695345],
[ 0.51548687, 0.2738187 , 0.12451008, 0.07451822, 0.12451008,
0.2738187 , 0.51548687],
[ 0.72668956, 0.48646962, 0.33961424, 0.2920419 , 0.33961424,
0.48646962, 0.72668956],
[ 1.06799812, 0.83180576, 0.6934727 , 0.645892 , 0.6934727 ,
0.83180576, 1.06799812]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 6.34187696, 6.18689857, 6.15537676, 6.13263668, 6.15537676,
6.18689857, 6.34187696],
[ 6.1667275 , 6.04409157, 5.9555343 , 5.96586226, 5.9555343 ,
6.04409157, 6.1667275 ],
[ 6.04113522, 5.96186983, 5.88482917, 5.87387645, 5.88482917,
5.96186983, 6.04113522],
[ 6.03838637, 5.91117189, 5.85034216, 0. , 5.85034216,
5.91117189, 6.03838637],
[ 6.04111884, 5.96188527, 5.88481675, 5.87387645, 5.88481675,
5.96188527, 6.04111884],
[ 6.16677535, 6.04409147, 5.9555607 , 5.96586226, 5.9555607 ,
6.04409147, 6.16677535],
[ 6.34199129, 6.18699823, 6.15538781, 6.13263668, 6.15538781,
6.18699823, 6.34199129]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: stable
# - Mech is NM
origin.setMechanism('NM')
origin._tectonic_region = 'Stable Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.11595412, 0.87047978, 0.72608143, 0.6763976 , 0.72608143,
0.87047978, 1.11595412],
[ 0.7606424 , 0.50965507, 0.35594865, 0.30612448, 0.35594865,
0.50965507, 0.7606424 ],
[ 0.5400275 , 0.28698884, 0.13052973, 0.0781228 , 0.13052973,
0.28698884, 0.5400275 ],
[ 0.46835876, 0.21071547, 0.05370847, 0. , 0.05370847,
0.21071547, 0.46835876],
[ 0.54011298, 0.28702933, 0.1305397 , 0.0781228 , 0.1305397 ,
0.28702933, 0.54011298],
[ 0.76081471, 0.50973231, 0.35596982, 0.30612448, 0.35596982,
0.50973231, 0.76081471],
[ 1.116207 , 0.87059985, 0.72611052, 0.6763976 , 0.72611052,
0.87059985, 1.116207 ]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 6.09163676, 5.92783781, 5.88815939, 5.8632258 , 5.88815939,
5.92783781, 6.09163676],
[ 5.9012656 , 5.76798442, 5.67370059, 5.68021406, 5.67370059,
5.76798442, 5.9012656 ],
[ 5.76720934, 5.67516593, 5.59187321, 5.57813972, 5.59187321,
5.67516593, 5.76720934],
[ 5.75981247, 5.62205686, 5.55427369, 0. , 5.55427369,
5.62205686, 5.75981247],
[ 5.76719951, 5.67518325, 5.59186206, 5.57813972, 5.59186206,
5.67518325, 5.76719951],
[ 5.90132265, 5.76798949, 5.67372705, 5.68021406, 5.67372705,
5.76798949, 5.90132265],
[ 6.09176251, 5.92794056, 5.88817184, 5.8632258 , 5.88817184,
5.92794056, 6.09176251]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
# Souce instance
# - Tectonic region: stable
# - Mech is SS
origin.setMechanism('SS')
origin._tectonic_region = 'Stable Shallow Crust'
dists = Distance.fromSites(gmpe, site, rupture)
dctx = dists.getDistanceContext()
rjb = np.array([[ 1.7978181 , 1.48474703, 1.28392745, 1.21396452, 1.28392745,
1.48474703, 1.7978181 ],
[ 1.3323943 , 0.97123526, 0.72919945, 0.64364445, 0.72919945,
0.97123526, 1.3323943 ],
[ 1.01846151, 0.61039475, 0.3191157 , 0.20751973, 0.3191157 ,
0.61039475, 1.01846151],
[ 0.90673813, 0.47477623, 0.15160737, 0. , 0.15160737,
0.47477623, 0.90673813],
[ 1.01859418, 0.61046522, 0.3191364 , 0.20751973, 0.3191364 ,
0.61046522, 1.01859418],
[ 1.33263554, 0.97135557, 0.72923321, 0.64364445, 0.72923321,
0.97135557, 1.33263554],
[ 1.79813761, 1.48490175, 1.28396831, 1.21396452, 1.28396831,
1.48490175, 1.79813761]])
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
rrup = np.array([[ 5.27459324, 5.06456452, 4.9821571 , 4.94467172, 4.9821571 ,
5.06456452, 5.27459324],
[ 5.00483041, 4.80820132, 4.67381918, 4.65867853, 4.67381918,
4.80820132, 5.00483041],
[ 4.81923672, 4.64680257, 4.514164 , 4.47986499, 4.514164 ,
4.64680257, 4.81923672],
[ 4.78581905, 4.57286829, 4.44979468, 0. , 4.44979468,
4.57286829, 4.78581905],
[ 4.81926166, 4.64683299, 4.51415954, 4.47986499, 4.51415954,
4.64683299, 4.81926166],
[ 5.00493679, 4.80823501, 4.67384847, 4.65867853, 4.67384847,
4.80823501, 5.00493679],
[ 5.27477487, 5.06468553, 4.98217732, 4.94467172, 4.98217732,
5.06468553, 5.27477487]])
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
def test(vs30file=None):
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
mysite = Sites.createFromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file, padding=True,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array(
[[ 409.14199829, 428.24468994, 395.90026855, 426.31658936,
427.53845215, 433.40481567, 436.59918213, 440.43664551,
413.60662842],
[ 423.60855103, 426.64892578, 398.89712524, 428.88549805,
428.78335571, 428.58578491, 430.54354858, 433.59750366,
415.18811035],
[ 391.67398071, 426.20635986, 425.57946777, 428.21954346,
426.06726074, 421.86233521, 423.53192139, 426.25296021,
365.48190308],
[ 385.00396729, 428.14602661, 430.05944824, 429.3427124 ,
426.13626099, 409.76391602, 383.07299805, 372.39117432,
426.48486328],
[ 356.68756104, 432.64077759, 434.55209351, 432.21600342,
395.53771973, 419.31866455, 421.67749023, 426.23449707,
427.32818604],
[ 337.0546875 , 345.14605713, 403.78097534, 385.49118042,
413.04779053, 428.22869873, 427.00268555, 426.8951416 ,
425.62023926],
[ 403.78884888, 336.48217773, 347.82220459, 425.96798706,
432.0640564 , 429.40097046, 427.74179077, 427.00006104,
419.5062561 ],
[ 420.07458496, 330.57504272, 392.33255005, 430.33862305,
432.01391602, 429.43969727, 427.30435181, 425.96151733,
426.15856934]])
np.testing.assert_allclose(grd, grd_target)
sc = mysite.getSitesContext()
scsamp = mysite.sampleFromSites(np.array([34.1, 34.111]),
np.array([-118.2, -118.222]))
xmin = -118.2
xmax = -118.12
ymin = 34.05
ymax = 34.1
dx = 0.0083
dy = 0.0083
mysite = Sites.createFromBounds(xmin, xmax, ymin, ymax, dx, dy,
vs30File=vs30file, padding=False,
resample=False)
grd = mysite.getVs30Grid().getData()
grd_target = np.array(
[[ 426.13626099, 409.76391602, 383.07299805, 372.39117432,
426.48486328, 422.45065308, 417.21685791, 410.43737793,
405.33862305, 400.5239563 , 396.03030396],
[ 395.53771973, 419.31866455, 421.67749023, 426.23449707,
427.32818604, 424.84860229, 415.17590332, 407.5760498 ,
404.54788208, 402.28500366, 398.95913696],
[ 413.04779053, 428.22869873, 427.00268555, 426.8951416 ,
425.62023926, 419.60952759, 411.7961731 , 407.53509521,
406.22122192, 405.31622314, 402.92575073],
[ 432.0640564 , 429.40097046, 427.74179077, 427.00006104,
419.5062561 , 411.10830688, 407.48901367, 406.53305054,
406.59658813, 406.24887085, 406.17044067],
[ 432.01391602, 429.43969727, 427.30435181, 425.96151733,
426.15856934, 427.56121826, 397.67102051, 399.21054077,
404.54968262, 407.18515015, 410.00823975],
[ 426.76913452, 428.86270142, 425.99606323, 423.5692749 ,
423.59835815, 425.92758179, 408.44885254, 406.55810547,
409.06945801, 413.75210571, 417.71130371],
[ 423.1892395 , 427.91104126, 424.53796387, 419.47485352,
418.177948 , 424.14065552, 428.57913208, 432.95300293,
427.77731323, 431.46524048, 442.75540161],
[ 410.56729126, 423.15557861, 424.48355103, 419.27658081,
418.60211182, 423.86721802, 428.06176758, 432.42089844,
438.54446411, 448.37237549, 462.25509644],
[ 405.86877441, 414.27923584, 419.53878784, 396.18017578,
414.54452515, 419.80047607, 425.19824219, 424.48919678,
424.72061157, 431.52270508, 432.84347534]])
np.testing.assert_allclose(grd, grd_target)
def test_distance_from_sites_source():
# Make sites instance
vs30file = os.path.join(shakedir, 'tests/data/Vs30_test.grd')
cx = -118.2
cy = 34.1
dx = 0.0083
dy = 0.0083
xspan = 0.0083 * 5
yspan = 0.0083 * 5
site = Sites.createFromCenter(cx, cy, xspan, yspan, dx, dy,
vs30File=vs30file,
padding=True, resample=False)
# Make souce instance
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.])
flt = Fault.fromTrace(lon0, lat0, lon1, lat1, z, W, dip)
event = {'lat': 34.1, 'lon': -118.2, 'depth': 1, 'mag': 6,
'id': '', 'locstring': '', 'type': 'U',
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone': 'UTC'}
source = Source(event, flt)
gmpelist = [AbrahamsonEtAl2014(), BergeThierryEtAl2003SIGMA()]
dists = Distance.fromSites(gmpelist, source, site)
dctx = dists.getDistanceContext()
rhypo = np.array(
[[4.91471497, 4.47602418, 4.13427127, 3.91492565, 3.83902646,
3.91492565, 4.13427127, 4.47602418, 4.91471497],
[4.25968568, 3.74498133, 3.32896405, 3.05225679, 2.95426722,
3.05225679, 3.32896405, 3.74498133, 4.25968568],
[3.7219197, 3.11965436, 2.60558436, 2.24124201, 2.10583262,
2.24124201, 2.60558436, 3.11965436, 3.7219197],
[3.35823105, 2.67523213, 2.05265767, 1.564393, 1.36331682,
1.564393, 2.05265767, 2.67523213, 3.35823105],
[3.22800413, 2.50973226, 1.83166664, 1.26045653, 1.,
1.26045653, 1.83166664, 2.50973226, 3.22800413],
[3.35850726, 2.67542717, 2.05277065, 1.56443006, 1.36331682,
1.56443006, 2.05277065, 2.67542717, 3.35850726],
[3.72241812, 3.11998886, 2.60576236, 2.24129374, 2.10583262,
2.24129374, 2.60576236, 3.11998886, 3.72241812],
[4.26033893, 3.74539929, 3.32917303, 3.05231378, 2.95426722,
3.05231378, 3.32917303, 3.74539929, 4.26033893]]
)
np.testing.assert_allclose(
rhypo, dctx.rhypo, rtol=0, atol=0.01)
rx = np.array(
[[-4.25168879e+00, -3.54281195e+00, -2.83395897e+00,
-2.12512986e+00, -1.41632463e+00, -7.07543303e-01,
1.21411306e-03, 7.09947601e-01, 1.41865714e+00],
[-3.89788718e+00, -3.18894046e+00, -2.48001760e+00,
-1.77111861e+00, -1.06224350e+00, -3.53392295e-01,
3.55434994e-01, 1.06423835e+00, 1.77301777e+00],
[-3.54408550e+00, -2.83506891e+00, -2.12607617e+00,
-1.41710732e+00, -7.08162347e-01, 7.58720005e-04,
7.09655868e-01, 1.41852908e+00, 2.12737835e+00],
[-3.19028373e+00, -2.48119729e+00, -1.77213470e+00,
-1.06309600e+00, -3.54081177e-01, 3.54909735e-01,
1.06387673e+00, 1.77281978e+00, 2.48173889e+00],
[-2.83648190e+00, -2.12732562e+00, -1.41819320e+00,
-7.09084651e-01, 2.56777675e-12, 7.09060743e-01,
1.41809756e+00, 2.12711045e+00, 2.83609938e+00],
[-2.48268001e+00, -1.77345390e+00, -1.06425166e+00,
-3.55073292e-01, 3.54081177e-01, 1.06321174e+00,
1.77231837e+00, 2.48140106e+00, 3.19045980e+00],
[-2.12887807e+00, -1.41958215e+00, -7.10310097e-01,
-1.06192604e-03, 7.08162347e-01, 1.41736271e+00,
2.12653914e+00, 2.83569163e+00, 3.54482016e+00],
[-1.77507608e+00, -1.06571037e+00, -3.56368521e-01,
3.52949440e-01, 1.06224350e+00, 1.77151365e+00,
2.48075986e+00, 3.18998213e+00, 3.89918045e+00]]
)
np.testing.assert_allclose(
rx, dctx.rx, rtol=0, atol=0.01)
rjb = np.array(
[[4.25806540e+00, 3.54812473e+00, 2.83820819e+00,
2.12831587e+00, 1.41844799e+00, 7.08605677e-01,
2.52145001e-03, 2.71336156e-03, 2.81274718e-03],
[3.90373176e+00, 3.19372137e+00, 2.48373511e+00,
1.77377308e+00, 1.06383562e+00, 3.53925643e-01,
2.25816823e-03, 2.45009861e-03, 2.54949398e-03],
[3.54939857e+00, 2.83931844e+00, 2.12926243e+00,
1.41923064e+00, 7.09223517e-01, 1.57594916e-03,
1.86044244e-03, 2.05239165e-03, 2.15179678e-03],
[3.21162971e+00, 2.48510934e+00, 1.77479025e+00,
1.06468863e+00, 3.54611655e-01, 1.04375185e-03,
1.32827303e-03, 1.52024106e-03, 1.61965594e-03],
[3.07587955e+00, 2.30690967e+00, 1.53793979e+00,
7.68969896e-01, 5.88918451e-12, 3.77111295e-04,
6.61660373e-04, 8.53647223e-04, 2.38384209e-01],
[3.21191809e+00, 2.48531877e+00, 1.79442084e+00,
1.20242597e+00, 8.54793253e-01, 5.62052963e-01,
2.69254693e-01, 5.26105100e-05, 5.93270976e-01],
[3.58897017e+00, 2.95646628e+00, 2.40489915e+00,
2.00231070e+00, 1.70958533e+00, 1.41681634e+00,
1.12398937e+00, 8.63761551e-01, 1.08872127e+00],
[4.14172611e+00, 3.60741953e+00, 3.17112489e+00,
2.85711592e+00, 2.56437623e+00, 2.27157856e+00,
1.97872291e+00, 1.78518260e+00, 1.90424524e+00]]
)
np.testing.assert_allclose(
rjb, dctx.rjb, rtol=0, atol=0.01)
ry0 = np.array(
[[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[3.15917743e-01, 2.29488608e-02, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[1.17233848e+00, 8.79340738e-01, 5.86285075e-01,
2.93171494e-01, 6.20905972e-12, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[2.02875906e+00, 1.73573247e+00, 1.44264795e+00,
1.14950551e+00, 8.56305149e-01, 5.63046877e-01,
2.69730699e-01, 0.00000000e+00, 0.00000000e+00],
[2.88517947e+00, 2.59212404e+00, 2.29901067e+00,
2.00583937e+00, 1.71261015e+00, 1.41932302e+00,
1.12597797e+00, 8.32575011e-01, 5.39114157e-01],
[3.74159969e+00, 3.44851542e+00, 3.15537321e+00,
2.86217307e+00, 2.56891499e+00, 2.27559900e+00,
1.98222508e+00, 1.68879326e+00, 1.39530352e+00]]
)
np.testing.assert_allclose(
ry0, dctx.ry0, rtol=0, atol=0.01)
rrup = np.array(
[[4.37398161, 3.68659567, 3.00969158, 2.35231374, 1.73674834,
1.22755262, 1.0025215, 1.22371894, 1.57836451],
[4.02976949, 3.34678672, 2.67788811, 2.03697073, 1.46129187,
1.06271102, 1.06352692, 1.40073832, 1.75541869],
[3.68743926, 3.01030105, 2.3526499, 1.73673635, 1.22706347,
1.00157564, 1.22283363, 1.57764099, 1.93235615],
[3.3634728, 2.67858182, 2.03712377, 1.46095502, 1.06170931,
1.06220616, 1.39958479, 1.75442695, 2.1091769],
[3.23412325, 2.51415965, 1.8343632, 1.26143652, 1.,
1.2212501, 1.57621925, 1.9310962, 2.28588093],
[3.36374812, 2.67877609, 2.05412785, 1.56384179, 1.3617346,
1.50608502, 1.77308319, 2.10764873, 2.46246823],
[3.72541099, 3.12078859, 2.6043486, 2.23799413, 2.09885629,
2.11696797, 2.23191013, 2.4299612, 2.69282837],
[4.26042286, 3.74318473, 3.32482368, 3.04635272, 2.9183523,
2.86659485, 2.88815116, 2.98141559, 3.13998993]]
)
np.testing.assert_allclose(
rrup, dctx.rrup, rtol=0, atol=0.01)
def test_station(tmpdir):
homedir = os.path.dirname(os.path.abspath(__file__))
datadir = os.path.abspath(os.path.join(homedir, '..', 'data',
'eventdata', 'Calexico', 'input'))
#
# Read the event, source, and rupture files and produce a Source object
#
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
eventfile = os.path.join(datadir, 'event.xml')
rupturefile = os.path.join(datadir, 'wei_fault.txt')
source_obj = Source.fromFile(eventfile, rupturefile=rupturefile)
#
# Set up the GMPE, IPE, and GMICE
#
gmpe_cy14 = ChiouYoungs2014()
gmpe = MultiGMPE.from_list([gmpe_cy14], [1.0])
gmice = WGRW12()
ipe = AllenEtAl2012()
#
#
#
rupture_ctx = source_obj.getRuptureContext([gmpe])
smdx = 0.0083333333
smdy = 0.0083333333
lonspan = 6.0
latspan = 4.0
vs30filename = os.path.join(datadir, '..', 'vs30', 'vs30.grd')
sites_obj_grid = Sites.fromCenter(
rupture_ctx.hypo_lon, rupture_ctx.hypo_lat, lonspan, latspan,
smdx, smdy, defaultVs30=760.0, vs30File=vs30filename,
vs30measured_grid=None, padding=False, resample=False
)
xmlfiles = [inputfile, dyfifile]
# dbfile = str(tmpdir.join('stations.db'))
dbfile = os.path.join(str(tmpdir), 'stations.db')
stations = StationList.fromXML(xmlfiles, dbfile, source_obj,
sites_obj_grid, gmpe, ipe, gmice)
df1 = stations.getStationDataframe(1, sort=True)
df2 = stations.getStationDataframe(0, sort=True)
#
# In case the test starts failing because of some minor change
# in one of the prediction or conversion equations (or roundoff
# or whatever), but the code is running correctly, uncomment
# these lines and re-run the test. Then, copy the new stations.db
# file into tests/data/eventdata/Calexico/database/. Then
# recomment these lines and rerun the test. It should succeed.
#
#shutil.copy(dbfile,'./stations.db')
#print(os.getcwd())
#
# We should probably check these dataframes against some established
# set, and also check the database against a known database.
#
ref_dbfile = os.path.join(datadir, '..', 'database', 'stations.db')
stations2 = StationList(ref_dbfile)
ref_df1 = stations2.getStationDataframe(1, sort=True)
ref_df2 = stations2.getStationDataframe(0, sort=True)
# assert ref_df1.equals(df1)
# assert ref_df2.equals(df2)
pdt.assert_frame_equal(df1, ref_df1)
pdt.assert_frame_equal(df2, ref_df2)
