def test_fromTrace():
xp0 = [0.0]
xp1 = [0.0]
yp0 = [0.0]
yp1 = [0.05]
zp = [0.0]
widths = [10.0]
dips = [45.0]
fault = Fault.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
reference='From J Smith, (personal communication)')
fstr = io.StringIO()
fault.writeFaultFile(fstr)
xp0 = [-121.81529, -121.82298]
xp1 = [-121.82298, -121.83068]
yp0 = [37.73707, 37.74233]
yp1 = [37.74233, 37.74758]
zp = [10, 15]
widths = [15.0, 20.0]
dips = [30.0, 45.0]
fault = Fault.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
reference='From J Smith, (personal communication)')
def test_plot_fault_wire3d():
ff = os.path.join(shakedir,
"tests/data/eventdata/hayward_RC_HN_HS_HE_Shaw09Mod_GEOL.txt")
flt = Fault.readFaultFile(ff)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plot_fault_wire3d(flt, ax)
return fig
def test_plot_fault_wire3d():
ff = os.path.join(
shakedir,
"tests/data/eventdata/hayward_RC_HN_HS_HE_Shaw09Mod_GEOL.txt")
flt = Fault.readFaultFile(ff)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
plot_fault_wire3d(flt, ax)
return fig
def test_misc():
# Make a fault
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)
fm = flt.getFaultAsMesh()
fa = flt.getFaultAsArrays()
ref = flt.getReference()
def test_misc():
# Make a fault
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)
fm = flt.getFaultAsMesh()
fa = flt.getFaultAsArrays()
ref = flt.getReference()
def _test_correct():
#this fault should parse correctly
fault_text = """#SOURCE: Barka, A., H. S. Akyz, E. Altunel, G. Sunal, Z. Akir, A. Dikbas, B. Yerli, R. Armijo, B. Meyer, J. B. d. Chabalier, T. Rockwell, J. R. Dolan, R. Hartleb, T. Dawson, S. Christofferson, A. Tucker, T. Fumal, R. Langridge, H. Stenner, W. Lettis, J. Bachhuber, and W. Page (2002). The Surface Rupture and Slip Distribution of the 17 August 1999 Izmit Earthquake (M 7.4), North Anatolian Fault, Bull. Seism. Soc. Am. 92, 43-60.
40.70985 29.33760 0
40.72733 29.51528 0
40.72933 29.51528 20
40.71185 29.33760 20
40.70985 29.33760 0
>
40.70513 29.61152 0
40.74903 29.87519 0
40.75103 29.87519 20
40.70713 29.61152 20
40.70513 29.61152 0
>
40.72582 29.88662 0
40.72336 30.11126 0
40.73432 30.19265 0
40.73632 30.19265 20
40.72536 30.11126 20
40.72782 29.88662 20
40.72582 29.88662 0
>
40.71210 30.30494 0
40.71081 30.46540 0
40.70739 30.56511 0
40.70939 30.56511 20
40.71281 30.46540 20
40.71410 30.30494 20
40.71210 30.30494 0
>
40.71621 30.57658 0
40.70068 30.63731 0
40.70268 30.63731 20
40.71821 30.57658 20
40.71621 30.57658 0
>
40.69947 30.72900 0
40.79654 30.93655 0
40.79854 30.93655 20
40.70147 30.72900 20
40.69947 30.72900 0
>
40.80199 30.94688 0
40.84501 31.01799 0
40.84701 31.01799 20
40.80399 30.94688 20
40.80199 30.94688 0"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
def test_fromTrace():
xp0 = [0.0]
xp1 = [0.0]
yp0 = [0.0]
yp1 = [0.05]
zp = [0.0]
widths = [10.0]
dips = [45.0]
fault = Fault.fromTrace(xp0, yp0, xp1, yp1, zp, widths,
dips, reference='From J Smith, (personal communication)')
fstr = io.StringIO()
fault.writeFaultFile(fstr)
xp0 = [-121.81529, -121.82298]
xp1 = [-121.82298, -121.83068]
yp0 = [37.73707, 37.74233]
yp1 = [37.74233, 37.74758]
zp = [10, 15]
widths = [15.0, 20.0]
dips = [30.0, 45.0]
fault = Fault.fromTrace(xp0, yp0, xp1, yp1, zp, widths,
dips, reference='From J Smith, (personal communication)')
def main(pargs):
nargin = len(pargs.coords)
if nargin < 6:
print 'You must specify at least two top edge points each with (x y z) coordinates.'
sys.exit(1)
if (nargin % 3) != 0:
print 'Each point must have 3 coordinates (x y z) per top edge point.'
sys.exit(1)
npoints = nargin/3
nquads = ((npoints*2 - 4)/2) + 1
if pargs.widths is None or len(pargs.widths) != nquads:
print 'You must specify %i widths' % nquads
sys.exit(1)
if pargs.dips is not None and pargs.depths is not None:
print 'You must specify %i depths or %i dips, not both.' % (nquads,nquads)
sys.exit(1)
x = np.array(pargs.coords[1::3])
y = np.array(pargs.coords[0::3])
z = np.array(pargs.coords[2::3])
fault = Fault.fromTrace(x,y,z,pargs.widths,pargs.dips)
if pargs.plotfile:
fig = plt.figure()
ax0 = fig.add_subplot(2,1,1)
ax1 = fig.add_subplot(2,1,2, projection='3d')
for quad in fault.getQuadrilaterals():
P0,P1,P2,P3 = quad
xp = np.array([P0.longitude,P1.longitude,P2.longitude,P3.longitude,P0.longitude])
yp = np.array([P0.latitude,P1.latitude,P2.latitude,P3.latitude,P0.latitude])
zp = np.array([-P0.depth,-P1.depth,-P2.depth,-P3.depth,-P0.depth])
ax0.plot(xp,yp)
ax0.set_xlabel('Longitude')
ax0.set_xlabel('Latitude')
ax1.plot(xp,yp,zp)
ax1.set_xlabel('Longitude')
ax1.set_xlabel('Latitude')
ax1.set_zlabel('Depth')
ax0.axis('equal')
ax1.axis('equal')
plt.savefig(pargs.plotfile)
if pargs.outfile:
fault.writeFaultFile(pargs.outfile)
def _test_northridge():
#this should fail!
fault_text = """
# Source: Wald, D. J., T. H. Heaton, and K. W. Hudnut (1996). The Slip History of the 1994 Northridge, California, Earthquake Determined from Strong-Motion, Teleseismic, GPS, and Leveling Data, Bull. Seism. Soc. Am. 86, S49-S70.
34.315 -118.421 5.000
34.401 -118.587 5.000
34.261 -118.693 20.427
34.175 -118.527 20.427
34.315 -118.421 5.000
"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
quad = fault.getQuadrilaterals()[0]
topdist = quad[0].distance(quad[1])
fault.multiplyFaultLength(2.0)
quad = fault.getQuadrilaterals()[0]
topdist2 = quad[0].distance(quad[1])
x = 1
def test_slip():
# Make a fault
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)
slp = get_quad_slip(flt.getQuadrilaterals()[0], 30).getArray()
slpd = np.array([0.80816457, 0.25350787, 0.53160491])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector(22, 30, 86).getArray()
slpd = np.array([0.82714003, 0.38830563, 0.49878203])
np.testing.assert_allclose(slp, slpd)
def test_slip():
# Make a fault
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)
slp = get_quad_slip(flt.getQuadrilaterals()[0], 30).getArray()
slpd = np.array([0.80816457, 0.25350787, 0.53160491])
np.testing.assert_allclose(slp, slpd)
slp = get_local_unit_slip_vector(22, 30, 86).getArray()
slpd = np.array([0.82714003, 0.38830563, 0.49878203])
np.testing.assert_allclose(slp, slpd)
def test_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_incorrect():
fault_text = """# Source: Ji, C., D. V. Helmberger, D. J. Wald, and K.-F. Ma (2003). Slip history and dynamic implications of the 1999 Chi-Chi, Taiwan, earthquake, J. Geophys. Res. 108, 2412, doi:10.1029/2002JB001764.
24.27980 120.72300 0
24.05000 121.00000 17
24.07190 121.09300 17
24.33120 121.04300 17
24.27980 120.72300 0
>
24.27980 120.72300 0
23.70000 120.68000 0
23.60400 120.97200 17
24.05000 121.00000 17
24.27980 120.72300 0
>
23.60400 120.97200 17
23.70000 120.68000 0
23.58850 120.58600 0
23.40240 120.78900 17
23.60400 120.97200 17"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
def test_incorrect():
fault_text = """# Source: Ji, C., D. V. Helmberger, D. J. Wald, and K.-F. Ma (2003). Slip history and dynamic implications of the 1999 Chi-Chi, Taiwan, earthquake, J. Geophys. Res. 108, 2412, doi:10.1029/2002JB001764.
24.27980 120.72300 0
24.05000 121.00000 17
24.07190 121.09300 17
24.33120 121.04300 17
24.27980 120.72300 0
>
24.27980 120.72300 0
23.70000 120.68000 0
23.60400 120.97200 17
24.05000 121.00000 17
24.27980 120.72300 0
>
23.60400 120.97200 17
23.70000 120.68000 0
23.58850 120.58600 0
23.40240 120.78900 17
23.60400 120.97200 17"""
cbuf = io.StringIO(fault_text)
with pytest.raises(ShakeMapException):
fault = Fault.readFaultFile(cbuf)
def test_northridge():
fault_text = """
# Source: Wald, D. J., T. H. Heaton, and K. W. Hudnut (1996). The Slip History of the 1994 Northridge, California, Earthquake Determined from Strong-Motion, Teleseismic, GPS, and Leveling Data, Bull. Seism. Soc. Am. 86, S49-S70.
34.315 -118.421 5.000
34.401 -118.587 5.000
34.261 -118.693 20.427
34.175 -118.527 20.427
34.315 -118.421 5.000
"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
strike = fault.getStrike()
np.testing.assert_allclose(strike, 122.06408, atol=0.001)
dip = fault.getDip()
np.testing.assert_allclose(dip, 40.20979, atol=0.001)
L = fault.getFaultLength()
np.testing.assert_allclose(L, 17.99198, atol=0.001)
W = fault.getWidth()
np.testing.assert_allclose(W, 23.93699, atol=0.001)
nq = fault.getNumQuads()
np.testing.assert_allclose(nq, 1)
ns = fault.getNumSegments()
np.testing.assert_allclose(ns, 1)
sind = fault._getSegmentIndex()
np.testing.assert_allclose(sind, [0])
ztor = fault.getTopOfRupture()
np.testing.assert_allclose(ztor, 5, atol=0.001)
itl = fault.getIndividualTopLengths()
np.testing.assert_allclose(itl, 17.9919846, atol=0.001)
iw = fault.getIndividualWidths()
np.testing.assert_allclose(iw, 23.93699668, atol=0.001)
lats = fault.getLats()
lats_d = np.array([34.315, 34.401, 34.261, 34.175, 34.315])
np.testing.assert_allclose(lats, lats_d, atol=0.001)
lons = fault.getLons()
lons_d = np.array([-118.421, -118.587, -118.693, -118.527, -118.421])
np.testing.assert_allclose(lons, lons_d, atol=0.001)
def test_northridge():
fault_text = """
# Source: Wald, D. J., T. H. Heaton, and K. W. Hudnut (1996). The Slip History of the 1994 Northridge, California, Earthquake Determined from Strong-Motion, Teleseismic, GPS, and Leveling Data, Bull. Seism. Soc. Am. 86, S49-S70.
34.315 -118.421 5.000
34.401 -118.587 5.000
34.261 -118.693 20.427
34.175 -118.527 20.427
34.315 -118.421 5.000
"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
strike = fault.getStrike()
np.testing.assert_allclose(strike, 122.06408, atol=0.001)
dip = fault.getDip()
np.testing.assert_allclose(dip, 40.20979, atol=0.001)
L = fault.getFaultLength()
np.testing.assert_allclose(L, 17.99198, atol=0.001)
W = fault.getWidth()
np.testing.assert_allclose(W, 23.93699, atol=0.001)
nq = fault.getNumQuads()
np.testing.assert_allclose(nq, 1)
ns = fault.getNumSegments()
np.testing.assert_allclose(ns, 1)
sind = fault._getSegmentIndex()
np.testing.assert_allclose(sind, [0])
ztor = fault.getTopOfRupture()
np.testing.assert_allclose(ztor, 5, atol=0.001)
itl = fault.getIndividualTopLengths()
np.testing.assert_allclose(itl, 17.9919846, atol=0.001)
iw = fault.getIndividualWidths()
np.testing.assert_allclose(iw, 23.93699668, atol=0.001)
lats = fault.getLats()
lats_d = np.array([34.315, 34.401, 34.261, 34.175, 34.315])
np.testing.assert_allclose(lats, lats_d, atol=0.001)
lons = fault.getLons()
lons_d = np.array([-118.421, -118.587, -118.693, -118.527, -118.421])
np.testing.assert_allclose(lons, lons_d, atol=0.001)
def _test_intensity():
datadir = os.path.abspath(os.path.join(
homedir, '..', 'data', 'eventdata', 'northridge'))
shakefile = os.path.join(datadir, 'northridge_grid.xml')
topofile = os.path.join(datadir, 'northridge_topo.grd')
faultfile = os.path.join(datadir, 'northridge_fault.txt')
cityfile = os.path.join(datadir, 'northridge_cities.txt')
coastfile = os.path.join(datadir, 'northridge_coastline.json')
countryfile = os.path.join(datadir, 'northridge_countries.json')
statefile = os.path.join(datadir, 'northridge_states.json')
lakefile = os.path.join(datadir, 'northridge_lakes.json')
oceanfile = os.path.join(datadir, 'northridge_ocean.json')
stationfile = os.path.join(datadir, 'northridge_stations.db')
roadfile = os.path.join(datadir, 'northridge_roads.json')
tancptfile = os.path.join(shakedir, 'shakemap', 'mapping', 'tan.cpt')
shakecptfile = os.path.join(
shakedir, 'shakemap', 'mapping', 'shakecpt.cpt')
layerdict = {'coast': coastfile,
'ocean': oceanfile,
'lake': lakefile,
'country': countryfile,
'roads': roadfile,
'state': statefile}
tancolormap = ColorPalette.fromPreset('shaketopo')
shakecolormap = ColorPalette.fromPreset('mmi')
cities = BasemapCities.loadFromCSV(cityfile)
shakemap = ShakeGrid.load(shakefile, adjust='res')
stations = StationList(stationfile)
fault = Fault.readFaultFile(faultfile)
edict = shakemap.getEventDict()
eventdict = {'lat': edict['lat'],
'lon': edict['lon'],
'depth': edict['depth'],
'mag': edict['magnitude'],
'time': edict['event_timestamp']}
source = Source(eventdict, fault)
maker = MapMaker(shakemap, topofile, stations,
fault, layerdict, source, cities)
# draw intensity map
outfolder = os.path.expanduser('~')
maker.setIntensityLayer('mmi')
maker.setIntensityGMTColorMap(shakecolormap)
intensity_map = maker.drawIntensityMap(outfolder)
print('Intensity map saved as: %s' % intensity_map)
# draw contour maps
maker.setContourGMTColorMap(tancolormap)
# Draw pgv contours
maker.setContourLayer('pgv')
contour_pgv_map = maker.drawContourMap(outfolder)
print('PGV contour map saved as: %s' % contour_pgv_map)
# Draw pga contours
maker.setContourLayer('pga')
contour_pga_map = maker.drawContourMap(outfolder)
print('PGA contour map saved as: %s' % contour_pga_map)
# Draw psa0.3 contours
maker.setContourLayer('psa03')
contour_psa03_map = maker.drawContourMap(outfolder)
print('PSA0.3 contour map saved as: %s' % contour_psa03_map)
# Draw psa1.0 contours
maker.setContourLayer('psa10')
contour_psa10_map = maker.drawContourMap(outfolder)
print('PSA1.0 contour map saved as: %s' % contour_psa10_map)
# Draw psa3.0 contours
maker.setContourLayer('psa30')
contour_psa30_map = maker.drawContourMap(outfolder)
print('PSA3.0 contour map saved as: %s' % contour_psa30_map)
xp1 = [-121.82298, -121.83068]
yp0 = [37.73707, 37.74233]
yp1 = [37.74233, 37.74758]
zp = [10, 15]
widths = [15.0, 20.0]
dips = [30.0, 45.0]
fault = Fault.fromTrace(xp0,
yp0,
xp1,
yp1,
zp,
widths,
dips,
reference='From J Smith, (personal communication)')
if __name__ == '__main__':
xp0 = np.array([-118.0])
xp1 = np.array([-118.0])
yp0 = np.array([34.0])
yp1 = np.array([34.5])
zp = np.array([5.0])
widths = np.array([10.0])
dips = np.array([45.0])
fault = Fault.fromTrace(xp0, yp0, xp1, yp1, zp, widths, dips)
_test_trace()
#_test_northridge()
#_test_correct()
# _test_incorrect()
def test_san_fernando():
# This is a challenging fault due to overlapping and discordant
# segments, as brought up by Graeme Weatherill. Our initial
# implementation put the origin on the wrong side of the fault.
x0 = np.array([7.1845, 7.8693])
y0 = np.array([-10.3793, -16.2096])
z0 = np.array([3.0000, 0.0000])
x1 = np.array([-7.8506, -7.5856])
y1 = np.array([-4.9073, -12.0682])
z1 = np.array([3.0000, 0.0000])
x2 = np.array([-4.6129, -5.5149])
y2 = np.array([3.9887, -4.3408])
z2 = np.array([16.0300, 8.0000])
x3 = np.array([10.4222, 9.9400])
y3 = np.array([-1.4833, -8.4823])
z3 = np.array([16.0300, 8.0000])
epilat = 34.44000
epilon = -118.41000
proj = geo.utils.get_orthographic_projection(
epilon-1, epilon+1, epilat+1, epilat-1)
lon0,lat0 = proj(x0, y0, reverse = True)
lon1,lat1 = proj(x1, y1, reverse = True)
lon2,lat2 = proj(x2, y2, reverse = True)
lon3,lat3 = proj(x3, y3, reverse = True)
flt = Fault.fromVertices(
lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3)
flt._segment_index = [0, 1]
# Make a source object; most of the 'event' values don't matter
event = {'lat': 0, 'lon': 0, 'depth':0, 'mag': 6.61,
'id':'', 'locstring':'', 'type':'U',
'time':ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone':'UTC'}
source = Source(event, flt)
# Grid of sites
buf = 0.25
lat = np.linspace(np.nanmin(flt._lat)-buf, np.nanmax(flt._lat)+buf, 10)
lon = np.linspace(np.nanmin(flt._lon)-buf, np.nanmax(flt._lon)+buf, 10)
lons, lats = np.meshgrid(lon, lat)
dep = np.zeros_like(lons)
x,y = proj(lon, lat)
fltx,flty = proj(flt._lon, flt._lat)
# Calculate U and T
dtypes = ['U', 'T']
dists = get_distance(dtypes, lats, lons, dep, source)
targetU = np.array(
[[ 29.37395812, 22.56039569, 15.74545461, 8.92543078,
2.09723735, -4.73938823, -11.58093887, -18.42177264,
-25.25743913, -32.08635501],
[ 31.84149137, 25.03129417, 18.22007124, 11.40292429,
4.57583886, -2.26009972, -9.09790123, -15.92911065,
-22.75071243, -29.56450963],
[ 34.30623138, 27.49382948, 20.67774678, 13.85111535,
7.0115472 , 0.16942111, -6.65327488, -13.45181115,
-20.24352643, -27.03530618],
[ 36.78170249, 29.96380633, 23.1270492 , 16.23906653,
9.32934682, 2.41729624, -4.2732657 , -10.94940844,
-17.703852 , -24.4792072 ],
[ 39.29233805, 32.49155866, 25.68380903, 18.73823089,
12.08780156, 5.99219619, -1.38387344, -8.28331275,
-15.08759643, -21.87909368],
[ 41.84662959, 35.09745097, 28.42432401, 21.98993679,
15.2994003 , 8.38037254, 1.3900846 , -5.5601922 ,
-12.4250749 , -19.24690137],
[ 44.41552101, 37.69652131, 31.0257236 , 24.38573309,
17.67059825, 10.84688716, 3.96604399, -2.920931 ,
-9.78152208, -16.6132751 ],
[ 46.97201328, 40.2558351 , 33.55821495, 26.85923974,
20.12416451, 13.33640001, 6.50905851, -0.33349597,
-7.17138975, -13.99568321],
[ 49.51154107, 42.79053584, 36.07536907, 29.35382731,
22.61099757, 15.83894006, 9.04135415, 2.22928601,
-4.58574545, -11.3959888 ],
[ 52.03832734, 45.31289877, 38.58842009, 31.85764151,
25.11309728, 18.35066231, 11.57145669, 4.78070229,
-2.01505508, -8.81029694]])
np.testing.assert_allclose(dists['U'], targetU)
targetT = np.array(
[[-40.32654805, -38.14066537, -35.95781299, -33.79265063,
-31.65892948, -29.56075203, -27.48748112, -25.41823592,
-23.33452174, -21.22822801],
[-32.28894353, -30.06603457, -27.83163648, -25.61482279,
-23.45367121, -21.36959238, -19.34738882, -17.33510593,
-15.28949735, -13.20224592],
[-24.30254163, -22.03532096, -19.70590091, -17.35907062,
-15.10840929, -13.02682541, -11.13554925, -9.25705749,
-7.26675455, -5.19396824],
[-16.41306482, -14.1418547 , -11.68888578, -8.9318195 ,
-6.39939727, -4.10984325, -2.85061088, -1.29211846,
0.68929792, 2.78115216],
[ -8.63784529, -6.5089946 , -4.32108309, -1.44275161,
-0.05102145, -0.20890633, 3.92700516, 6.36977183,
8.55572399, 10.72128633],
[ -0.88135778, 1.06766314, 2.77955566, 3.8241835 ,
5.99212478, 8.76823285, 11.54715599, 14.0961506 ,
16.4200502 , 18.65346494],
[ 6.98140207, 8.91888936, 10.77724993, 12.6499521 ,
14.79454638, 17.18482779, 19.63520498, 22.03525644,
24.35152986, 26.60592498],
[ 14.95635952, 16.95134069, 18.94768299, 20.99811237,
23.15975573, 25.42700742, 27.74302905, 30.0547134 ,
32.33583361, 34.58421221],
[ 22.9921068 , 25.0353212 , 27.09829391, 29.20364631,
31.3678744 , 33.58684524, 35.8383652 , 38.09736043,
40.34713771, 42.58152772],
[ 31.05186177, 33.1252095 , 35.21960344, 37.34488267,
39.50633206, 41.70076344, 43.91762786, 46.14415669,
48.37021739, 50.59029205]])
np.testing.assert_allclose(dists['T'], targetT)
def _test_intensity():
datadir = os.path.abspath(
os.path.join(homedir, '..', 'data', 'eventdata', 'northridge'))
shakefile = os.path.join(datadir, 'northridge_grid.xml')
topofile = os.path.join(datadir, 'northridge_topo.grd')
faultfile = os.path.join(datadir, 'northridge_fault.txt')
cityfile = os.path.join(datadir, 'northridge_cities.txt')
coastfile = os.path.join(datadir, 'northridge_coastline.json')
countryfile = os.path.join(datadir, 'northridge_countries.json')
statefile = os.path.join(datadir, 'northridge_states.json')
lakefile = os.path.join(datadir, 'northridge_lakes.json')
oceanfile = os.path.join(datadir, 'northridge_ocean.json')
stationfile = os.path.join(datadir, 'northridge_stations.db')
roadfile = os.path.join(datadir, 'northridge_roads.json')
tancptfile = os.path.join(shakedir, 'shakemap', 'mapping', 'tan.cpt')
shakecptfile = os.path.join(shakedir, 'shakemap', 'mapping',
'shakecpt.cpt')
layerdict = {
'coast': coastfile,
'ocean': oceanfile,
'lake': lakefile,
'country': countryfile,
'roads': roadfile,
'state': statefile
}
tancolormap = GMTColorMap.loadFromCPT(tancptfile)
shakecolormap = GMTColorMap.loadFromCPT(shakecptfile)
cities = BasemapCities.loadFromCSV(cityfile)
shakemap = ShakeGrid.load(shakefile, adjust='res')
stations = StationList(stationfile)
fault = Fault.readFaultFile(faultfile)
edict = shakemap.getEventDict()
eventdict = {
'lat': edict['lat'],
'lon': edict['lon'],
'depth': edict['depth'],
'mag': edict['magnitude'],
'time': edict['event_timestamp']
}
source = Source(eventdict, fault)
maker = MapMaker(shakemap, topofile, stations, fault, layerdict, source,
cities)
# draw intensity map
outfolder = os.path.expanduser('~')
maker.setIntensityLayer('mmi')
maker.setIntensityGMTColorMap(shakecolormap)
intensity_map = maker.drawIntensityMap(outfolder)
print('Intensity map saved as: %s' % intensity_map)
# draw contour maps
maker.setContourGMTColorMap(tancolormap)
# Draw pgv contours
maker.setContourLayer('pgv')
contour_pgv_map = maker.drawContourMap(outfolder)
print('PGV contour map saved as: %s' % contour_pgv_map)
# Draw pga contours
maker.setContourLayer('pga')
contour_pga_map = maker.drawContourMap(outfolder)
print('PGA contour map saved as: %s' % contour_pga_map)
# Draw psa0.3 contours
maker.setContourLayer('psa03')
contour_psa03_map = maker.drawContourMap(outfolder)
print('PSA0.3 contour map saved as: %s' % contour_psa03_map)
# Draw psa1.0 contours
maker.setContourLayer('psa10')
contour_psa10_map = maker.drawContourMap(outfolder)
print('PSA1.0 contour map saved as: %s' % contour_psa10_map)
# Draw psa3.0 contours
maker.setContourLayer('psa30')
contour_psa30_map = maker.drawContourMap(outfolder)
print('PSA3.0 contour map saved as: %s' % contour_psa30_map)
def test_chichi():
print('Testing Chi-Chi...')
# read in fault file
f = '../data/0137A.POL'
i0 = np.arange(0, 9 * 11 * 3, 11)
i1 = i0 + 10
cs = zip(i0, i1)
df = pd.read_fwf(f, cs, skiprows=2, nrows=5, header=None)
mat = df.as_matrix()
ix = np.arange(0, 9 * 3, 3)
iy = ix + 1
iz = ix + 2
x0 = mat[0, ix]
x1 = mat[1, ix]
x2 = mat[2, ix]
x3 = mat[3, ix]
y0 = mat[0, iy]
y1 = mat[1, iy]
y2 = mat[2, iy]
y3 = mat[3, iy]
# Depth, positive down
z0 = np.abs(mat[0, iz])
z1 = np.abs(mat[1, iz])
z2 = np.abs(mat[2, iz])
z3 = np.abs(mat[3, iz])
epilat = 23.85
epilon = 120.82
proj = get_orthographic_projection(epilon - 1, epilon + 1, epilat + 1,
epilat - 1)
lon0, lat0 = proj(x0, y0, reverse=True)
lon1, lat1 = proj(x1, y1, reverse=True)
lon2, lat2 = proj(x2, y2, reverse=True)
lon3, lat3 = proj(x3, y3, reverse=True)
flt = Fault.fromVertices(lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2,
lon3, lat3, z3)
ask14 = AbrahamsonEtAl2014()
# event information doesn't matter...
event = {
'lat': 0,
'lon': 0,
'depth': 0,
'mag': 7,
'id': '',
'locstring': '',
'type': 'U',
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone': 'UTC'
}
source = Source(event, flt)
# Get NGA distances
distfile = '../data/NGAW2_distances.csv'
df = pd.read_csv(distfile)
df2 = df.loc[df['EQID'] == 137]
slat = df2['Station Latitude'].as_matrix()
slon = df2['Station Longitude'].as_matrix()
sdep = np.zeros(slat.shape)
nga_repi = df2['EpiD (km)'].as_matrix()
nga_rhypo = df2['HypD (km)'].as_matrix()
nga_rrup = df2['ClstD (km)'].as_matrix()
nga_rjb = df2['Joyner-Boore Dist. (km)'].as_matrix()
nga_rx = df2['T'].as_matrix()
dist = Distance(ask14, source, slat, slon, sdep)
dctx = dist.getDistanceContext()
fig = plt.figure(figsize=(8, 8))
plt.scatter(nga_rjb, dctx.rjb, alpha=0.5, facecolors='none')
plt.plot([0, nga_rjb.max()], [0, dctx.rjb.max()], 'b')
plt.savefig('Chi-Chi_Rjb.png')
fig = plt.figure(figsize=(8, 8))
plt.scatter(nga_rrup, dctx.rrup, alpha=0.5, facecolors='none')
plt.plot([0, nga_rrup.max()], [0, dctx.rrup.max()], 'b')
plt.savefig('Chi-Chi_Rrup.png')
fig = plt.figure(figsize=(8, 8))
plt.scatter(nga_rx, dctx.rx, alpha=0.5, facecolors='none')
plt.plot([nga_rx.min(), nga_rx.max()],
[dctx.rx.min(), dctx.rx.max()], 'b')
plt.savefig('Chi-Chi_Rx.png')
def parse_complicated_fault():
fault_text = """#SOURCE: Barka, A., H. S. Akyz, E. Altunel, G. Sunal, Z. Akir, A. Dikbas, B. Yerli, R. Armijo, B. Meyer, J. B. d. Chabalier, T. Rockwell, J. R. Dolan, R. Hartleb, T. Dawson, S. Christofferson, A. Tucker, T. Fumal, R. Langridge, H. Stenner, W. Lettis, J. Bachhuber, and W. Page (2002). The Surface Rupture and Slip Distribution of the 17 August 1999 Izmit Earthquake (M 7.4), North Anatolian Fault, Bull. Seism. Soc. Am. 92, 43-60.
40.70985 29.33760 0
40.72733 29.51528 0
40.72933 29.51528 20
40.71185 29.33760 20
40.70985 29.33760 0
>
40.70513 29.61152 0
40.74903 29.87519 0
40.75103 29.87519 20
40.70713 29.61152 20
40.70513 29.61152 0
>
40.72582 29.88662 0
40.72336 30.11126 0
40.73432 30.19265 0
40.73632 30.19265 20
40.72536 30.11126 20
40.72782 29.88662 20
40.72582 29.88662 0
>
40.71210 30.30494 0
40.71081 30.46540 0
40.70739 30.56511 0
40.70939 30.56511 20
40.71281 30.46540 20
40.71410 30.30494 20
40.71210 30.30494 0
>
40.71621 30.57658 0
40.70068 30.63731 0
40.70268 30.63731 20
40.71821 30.57658 20
40.71621 30.57658 0
>
40.69947 30.72900 0
40.79654 30.93655 0
40.79854 30.93655 20
40.70147 30.72900 20
40.69947 30.72900 0
>
40.80199 30.94688 0
40.84501 31.01799 0
40.84701 31.01799 20
40.80399 30.94688 20
40.80199 30.94688 0"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
strike = fault.getStrike()
np.testing.assert_allclose(strike, -100.464330, atol=0.001)
dip = fault.getDip()
np.testing.assert_allclose(dip, 89.3985, atol=0.001)
L = fault.getFaultLength()
np.testing.assert_allclose(L, 119.5578, atol=0.001)
W = fault.getWidth()
np.testing.assert_allclose(W, 20.001, atol=0.001)
nq = fault.getNumQuads()
np.testing.assert_allclose(nq, 9)
ns = fault.getNumSegments()
np.testing.assert_allclose(ns, 7)
sind = fault._getSegmentIndex()
np.testing.assert_allclose(sind, [0, 1, 2, 2, 3, 3, 4, 5, 6])
ztor = fault.getTopOfRupture()
np.testing.assert_allclose(ztor, 0, atol=0.001)
itl = fault.getIndividualTopLengths()
itl_d = np.array([15.13750778, 22.80237887, 18.98053425, 6.98263853,
13.55978731, 8.43444811, 5.41399812, 20.57788056,
7.66869463])
np.testing.assert_allclose(itl, itl_d, atol=0.001)
iw = fault.getIndividualWidths()
iw_d = np.array([20.00122876, 20.00122608, 20.00120173, 20.00121028,
20.00121513, 20.00121568, 20.00107293, 20.00105498,
20.00083348])
np.testing.assert_allclose(iw, iw_d, atol=0.001)
lats = fault.getLats()
lats_d = np.array([40.70985, 40.72733, 40.72933, 40.71185, 40.70985,
np.nan, 40.70513, 40.74903, 40.75103, 40.70713,
40.70513, np.nan, 40.72582, 40.72336, 40.73432,
40.73632, 40.72536, 40.72782, 40.72582, np.nan,
40.7121, 40.71081, 40.70739, 40.70939, 40.71281,
40.7141, 40.7121, np.nan, 40.71621, 40.70068,
40.70268, 40.71821, 40.71621, np.nan, 40.69947,
40.79654, 40.79854, 40.70147, 40.69947, np.nan,
40.80199, 40.84501, 40.84701, 40.80399, 40.80199])
np.testing.assert_allclose(lats, lats_d, atol=0.001)
lons = fault.getLons()
lons_d = np.array([29.3376, 29.51528, 29.51528, 29.3376, 29.3376,
np.nan, 29.61152, 29.87519, 29.87519, 29.61152,
29.61152, np.nan, 29.88662, 30.11126, 30.19265,
30.19265, 30.11126, 29.88662, 29.88662, np.nan,
30.30494, 30.4654, 30.56511, 30.56511, 30.4654,
30.30494, 30.30494, np.nan, 30.57658, 30.63731,
30.63731, 30.57658, 30.57658, np.nan, 30.729,
30.93655, 30.93655, 30.729, 30.729, np.nan,
30.94688, 31.01799, 31.01799, 30.94688, 30.94688])
np.testing.assert_allclose(lons, lons_d, atol=0.001)
def parse_complicated_fault():
fault_text = """#SOURCE: Barka, A., H. S. Akyz, E. Altunel, G. Sunal, Z. Akir, A. Dikbas, B. Yerli, R. Armijo, B. Meyer, J. B. d. Chabalier, T. Rockwell, J. R. Dolan, R. Hartleb, T. Dawson, S. Christofferson, A. Tucker, T. Fumal, R. Langridge, H. Stenner, W. Lettis, J. Bachhuber, and W. Page (2002). The Surface Rupture and Slip Distribution of the 17 August 1999 Izmit Earthquake (M 7.4), North Anatolian Fault, Bull. Seism. Soc. Am. 92, 43-60.
40.70985 29.33760 0
40.72733 29.51528 0
40.72933 29.51528 20
40.71185 29.33760 20
40.70985 29.33760 0
>
40.70513 29.61152 0
40.74903 29.87519 0
40.75103 29.87519 20
40.70713 29.61152 20
40.70513 29.61152 0
>
40.72582 29.88662 0
40.72336 30.11126 0
40.73432 30.19265 0
40.73632 30.19265 20
40.72536 30.11126 20
40.72782 29.88662 20
40.72582 29.88662 0
>
40.71210 30.30494 0
40.71081 30.46540 0
40.70739 30.56511 0
40.70939 30.56511 20
40.71281 30.46540 20
40.71410 30.30494 20
40.71210 30.30494 0
>
40.71621 30.57658 0
40.70068 30.63731 0
40.70268 30.63731 20
40.71821 30.57658 20
40.71621 30.57658 0
>
40.69947 30.72900 0
40.79654 30.93655 0
40.79854 30.93655 20
40.70147 30.72900 20
40.69947 30.72900 0
>
40.80199 30.94688 0
40.84501 31.01799 0
40.84701 31.01799 20
40.80399 30.94688 20
40.80199 30.94688 0"""
cbuf = io.StringIO(fault_text)
fault = Fault.readFaultFile(cbuf)
strike = fault.getStrike()
np.testing.assert_allclose(strike, -100.464330, atol=0.001)
dip = fault.getDip()
np.testing.assert_allclose(dip, 89.3985, atol=0.001)
L = fault.getFaultLength()
np.testing.assert_allclose(L, 119.5578, atol=0.001)
W = fault.getWidth()
np.testing.assert_allclose(W, 20.001, atol=0.001)
nq = fault.getNumQuads()
np.testing.assert_allclose(nq, 9)
ns = fault.getNumSegments()
np.testing.assert_allclose(ns, 7)
sind = fault._getSegmentIndex()
np.testing.assert_allclose(sind, [0, 1, 2, 2, 3, 3, 4, 5, 6])
ztor = fault.getTopOfRupture()
np.testing.assert_allclose(ztor, 0, atol=0.001)
itl = fault.getIndividualTopLengths()
itl_d = np.array([
15.13750778, 22.80237887, 18.98053425, 6.98263853, 13.55978731,
8.43444811, 5.41399812, 20.57788056, 7.66869463
])
np.testing.assert_allclose(itl, itl_d, atol=0.001)
iw = fault.getIndividualWidths()
iw_d = np.array([
20.00122876, 20.00122608, 20.00120173, 20.00121028, 20.00121513,
20.00121568, 20.00107293, 20.00105498, 20.00083348
])
np.testing.assert_allclose(iw, iw_d, atol=0.001)
lats = fault.getLats()
lats_d = np.array([
40.70985, 40.72733, 40.72933, 40.71185, 40.70985, np.nan, 40.70513,
40.74903, 40.75103, 40.70713, 40.70513, np.nan, 40.72582, 40.72336,
40.73432, 40.73632, 40.72536, 40.72782, 40.72582, np.nan, 40.7121,
40.71081, 40.70739, 40.70939, 40.71281, 40.7141, 40.7121, np.nan,
40.71621, 40.70068, 40.70268, 40.71821, 40.71621, np.nan, 40.69947,
40.79654, 40.79854, 40.70147, 40.69947, np.nan, 40.80199, 40.84501,
40.84701, 40.80399, 40.80199
])
np.testing.assert_allclose(lats, lats_d, atol=0.001)
lons = fault.getLons()
lons_d = np.array([
29.3376, 29.51528, 29.51528, 29.3376, 29.3376, np.nan, 29.61152,
29.87519, 29.87519, 29.61152, 29.61152, np.nan, 29.88662, 30.11126,
30.19265, 30.19265, 30.11126, 29.88662, 29.88662, np.nan, 30.30494,
30.4654, 30.56511, 30.56511, 30.4654, 30.30494, 30.30494, np.nan,
30.57658, 30.63731, 30.63731, 30.57658, 30.57658, np.nan, 30.729,
30.93655, 30.93655, 30.729, 30.729, np.nan, 30.94688, 31.01799,
31.01799, 30.94688, 30.94688
])
np.testing.assert_allclose(lons, lons_d, atol=0.001)
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_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_chichi():
print('Testing Chi-Chi...')
# read in fault file
f = '../data/0137A.POL'
i0 = np.arange(0, 9*11*3, 11)
i1 = i0 + 10
cs = zip(i0, i1)
df = pd.read_fwf(f, cs, skiprows = 2, nrows = 5, header = None)
mat = df.as_matrix()
ix = np.arange(0, 9*3, 3)
iy = ix + 1
iz = ix + 2
x0 = mat[0, ix]
x1 = mat[1, ix]
x2 = mat[2, ix]
x3 = mat[3, ix]
y0 = mat[0, iy]
y1 = mat[1, iy]
y2 = mat[2, iy]
y3 = mat[3, iy]
# Depth, positive down
z0 = np.abs(mat[0, iz])
z1 = np.abs(mat[1, iz])
z2 = np.abs(mat[2, iz])
z3 = np.abs(mat[3, iz])
epilat = 23.85
epilon = 120.82
proj = get_orthographic_projection(
epilon-1, epilon+1, epilat+1, epilat-1)
lon0,lat0 = proj(x0, y0, reverse = True)
lon1,lat1 = proj(x1, y1, reverse = True)
lon2,lat2 = proj(x2, y2, reverse = True)
lon3,lat3 = proj(x3, y3, reverse = True)
flt = Fault.fromVertices(
lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3)
ask14 = AbrahamsonEtAl2014()
# event information doesn't matter...
event = {'lat': 0, 'lon': 0, 'depth':0, 'mag': 7,
'id':'', 'locstring':'', 'type':'U',
'time':ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone':'UTC'}
source = Source(event, flt)
# Get NGA distances
distfile = '../data/NGAW2_distances.csv'
df = pd.read_csv(distfile)
df2 = df.loc[df['EQID'] == 137]
slat = df2['Station Latitude'].as_matrix()
slon = df2['Station Longitude'].as_matrix()
sdep = np.zeros(slat.shape)
nga_repi = df2['EpiD (km)'].as_matrix()
nga_rhypo = df2['HypD (km)'].as_matrix()
nga_rrup = df2['ClstD (km)'].as_matrix()
nga_rjb = df2['Joyner-Boore Dist. (km)'].as_matrix()
nga_rx = df2['T'].as_matrix()
dist = Distance(ask14, source, slat, slon, sdep)
dctx = dist.getDistanceContext()
fig = plt.figure(figsize=(8,8))
plt.scatter(nga_rjb, dctx.rjb, alpha = 0.5, facecolors='none')
plt.plot([0, nga_rjb.max()], [0, dctx.rjb.max()], 'b');
plt.savefig('Chi-Chi_Rjb.png')
fig = plt.figure(figsize=(8,8))
plt.scatter(nga_rrup, dctx.rrup, alpha = 0.5, facecolors='none')
plt.plot([0, nga_rrup.max()], [0, dctx.rrup.max()], 'b');
plt.savefig('Chi-Chi_Rrup.png')
fig = plt.figure(figsize=(8,8))
plt.scatter(nga_rx, dctx.rx, alpha = 0.5, facecolors='none')
plt.plot([nga_rx.min(), nga_rx.max()],
[dctx.rx.min(), dctx.rx.max()], 'b');
plt.savefig('Chi-Chi_Rx.png')
def test_chichi_with_get_distance():
# read in fault file
f = os.path.join(shakedir, 'tests/data/0137A.POL')
i0 = np.arange(0, 9 * 11 * 3, 11)
i1 = i0 + 10
cs = list(zip(i0, i1))
df = pd.read_fwf(f, cs, skiprows=2, nrows=5, header=None)
mat = df.as_matrix()
ix = np.arange(0, 9 * 3, 3)
iy = ix + 1
iz = ix + 2
x0 = mat[0, ix]
x1 = mat[1, ix]
x2 = mat[2, ix]
x3 = mat[3, ix]
y0 = mat[0, iy]
y1 = mat[1, iy]
y2 = mat[2, iy]
y3 = mat[3, iy]
# Depth, positive down
z0 = np.abs(mat[0, iz])
z1 = np.abs(mat[1, iz])
z2 = np.abs(mat[2, iz])
z3 = np.abs(mat[3, iz])
epilat = 23.85
epilon = 120.82
proj = get_orthographic_projection(
epilon - 1, epilon + 1, epilat + 1, epilat - 1)
lon0, lat0 = proj(x0, y0, reverse=True)
lon1, lat1 = proj(x1, y1, reverse=True)
lon2, lat2 = proj(x2, y2, reverse=True)
lon3, lat3 = proj(x3, y3, reverse=True)
flt = Fault.fromVertices(
lon0, lat0, z0, lon1, lat1, z1, lon2, lat2, z2, lon3, lat3, z3)
# event information doesn't matter except hypocenter
event = {'lat': 23.85, 'lon': 120.82, 'depth': 8, 'mag': 7.62,
'id': '', 'locstring': '', 'type': 'U',
'time': ShakeDateTime.utcfromtimestamp(int(time.time())),
'timezone': 'UTC'}
source = Source(event, flt)
# Get NGA distances
distfile = os.path.join(shakedir, 'tests/data/NGAW2_distances.csv')
df = pd.read_csv(distfile)
df2 = df.loc[df['EQID'] == 137]
slat = df2['Station Latitude'].as_matrix()
slon = df2['Station Longitude'].as_matrix()
sdep = np.zeros(slat.shape)
nga_repi = df2['EpiD (km)'].as_matrix()
nga_rhypo = df2['HypD (km)'].as_matrix()
nga_rrup = df2['ClstD (km)'].as_matrix()
nga_rjb = df2['Joyner-Boore Dist. (km)'].as_matrix()
nga_rx = df2['T'].as_matrix()
nga_T = df2['T'].as_matrix()
nga_U = df2['U'].as_matrix()
test_ry = np.array([
-49.25445446, -76.26871272, -37.1288192, -53.47792996,
-50.30711637, -63.96322125, -61.01988704, -81.2001781,
-76.00646939, -74.39038054, -92.23617124, -90.66976945,
-89.68551411, -102.98798328, -114.70036085, -29.83636082,
-28.50133134, -27.86922916, -36.00619214, -44.68826209,
-47.64580208, -53.92619079, -59.11962858, -55.90584822,
-55.00772025, -48.81756715, -59.27542007, -62.13633659,
-70.0673351, -75.96977638, -61.6959293, -60.34564074,
-81.49792285, -78.75933138, -80.80533738, -85.24473008,
-94.07519297, -93.75010471, -96.87089883, -100.06112271,
-98.86980873, -95.92330113, -107.44086722, -119.1065369,
-120.60405905, -113.42995442, -115.94930662, -115.2398216,
-107.37840927, -49.25445446, -48.78386688, -108.49133002,
-88.03303353, -44.66653428, -81.04476548, -38.26801619,
-70.51178983, -69.15679931, -74.74562139, -86.51133446,
-27.62153029, -48.33279375, -30.0808298, -113.98345018,
-97.96609537, -87.9863122, -39.45970018, -80.1387617,
-42.27121388, -82.05027834, -81.55987067, -81.55987067,
-107.25255717, 67.62695516, -3.27797047, -197.98554369,
82.30996151, 18.42180605, -22.88851072, -35.75245916,
-19.54788146, -18.19780517, 19.85077702, 20.33310282,
19.95448398, 20.55508903, 18.17428572, 17.87997374,
16.97323804, 16.0025885, 13.88001846, 18.42180605,
-3.27797047, 51.43098894, 28.97695533, -53.20579538,
38.7537468, 33.48878882, 26.25189111, 22.54251612,
13.37141837, -5.80928302, -6.68056794, -14.50860117,
-15.23992093, -27.63281952, -11.66075049, -36.94595337,
-40.97168031, -41.2814342, -48.64456898, -61.55777751,
-11.15038984, -17.16482959, 55.84202839, 36.78540588,
21.18550074, 19.14658833, 19.22680282, 5.76327358,
-47.45309937, -44.33194991, -55.15852372, 37.33066096,
37.64135657, 14.31598698, 4.60495737, 6.87107021,
18.42180605, 113.59285783, 109.06420877, 104.23416509,
99.21599973, 95.25204545, 90.29487934, 86.26977557,
95.28705209, 87.12907925, 101.40561896, 96.68858152,
92.90287952, 100.36659012, 97.19448577, 92.8627461,
85.01448355, 93.36767736, 96.90824009, 86.48002825,
88.71037964, 106.17282325, 102.56142319, 97.60004093,
99.61798574, 97.36337239, 94.22000798, 86.99488734,
90.05981676, 90.51189502, 100.7166391, 100.31931988,
67.62695516, 94.15062409, 87.77053675, 124.21806013,
99.23108884, 101.48199452, 92.63771423, 78.88723272,
72.7261356, 80.58682246, 73.30258213, 70.20783518,
60.57963211, -87.72265602, -148.10933308, -150.41334959,
-144.12558375, -145.5625388, -132.09479688, -135.12980144,
-121.10883695, -143.75755221, -117.73616176, -115.28563276,
-138.79652905, -143.10405603, -151.78419035, -159.75299736,
-149.69457229, -175.20332448, -181.00970647, -188.86536942,
-176.88178468, -194.20978527, -204.54944453, -161.04413103,
-197.98554369, -96.74089367, -133.49237232, -84.71198922,
-164.97719097, -202.48241157, -74.54550169, -147.37402934,
-144.64074441, -147.94282804, -122.80976842, -133.1671346,
-136.3051809, -113.93174768, -151.02125407, -146.5198829,
-156.19720713, -126.06138725, -131.44422964, -197.62591198,
-204.42320856, -149.84576063, -121.56474664, -130.99947339,
-148.41767074, -145.28448367, 104.58903799, 82.1649906,
67.69977397, 39.46989193, -69.00949731, -133.49237232,
-128.264754, -84.71198922, -108.49133002, 119.86128724,
122.73556155, 126.28254009, 125.12436373, 123.32498578,
123.8337768, 121.39931427, 121.48412837, 122.03669249,
122.59675818, 119.54338365, 120.33961222, 120.69581745,
116.96928355, 117.6687724, 116.62277942, 115.39650689,
112.60751523, 109.82643069, 108.2500678, 130.9143614,
126.50049543, 112.76229057, 132.76840098, 107.27099883,
128.16063464, 123.83157143, 120.46711628, 112.55756637,
135.59953867, 136.66138116, 136.98573162, 134.04528777,
116.27744752, 129.2794577, 119.13550981, 124.67196321,
130.9728774, 130.9039439, 128.70028371, 130.04592892,
140.21819548, 140.60370422, 113.37585901, 123.21523323,
123.88149248, 128.56894995, 128.45186255, 118.74080853,
126.71189149, 119.79833338, 130.00866791, -160.01242472,
13.55424709, 110.26938756, 97.71987778, 110.93671325,
108.71965725, 105.03432063, 106.36049687, 99.27569343,
115.06168146, 77.00378531, 81.50139192, 92.15605815,
79.94311644, 83.16892433, 52.23389149, 50.97110177,
67.95167063, 63.43930833, 40.20494692, 43.22936492,
47.21513635, 38.94380012, 53.85489136, 56.69935207,
48.07036522, 64.46887891, 14.98020647, 17.35046801,
16.15236633, 14.41062231, 19.99605739, 18.31076661,
15.07058247, 12.34339267, 13.57621451, 14.72685201,
22.04539325, 20.47982142, 9.66768974, 8.05139052,
29.22924869, 3.75876894, 7.8610467, 29.20272495,
15.19325822, -2.38981899, 5.58349359, -0.62239018,
-4.38178769, -11.43651893, -20.07048519, -16.0588668,
82.30996151, 13.55424709, 104.49355303, -11.29628168,
82.1649906, 34.22207039, 38.08490923, -10.15855131,
111.0308369, 81.78397481, 73.56334665, 81.27164139,
74.55979012, 16.08437955, 23.8203941, 24.68836209,
28.73767914, 21.06714416, 19.44159522, 4.62135887,
3.41771413, 5.051121, -6.81834189, 6.40341853,
-0.35693923, -17.74409367, -8.91759817, -18.05278804,
7.70695248, -5.52733835, -16.02924961, -4.54310111,
-22.84234773, -1.71908199, 39.46989193, -14.74007542,
23.59992543, -10.49966883, -11.47733869, -22.8200901,
-9.72486483, 95.96997763, -115.36487081, -52.88924268,
-90.2275069, -132.22657274, -100.52455976, -115.24052939,
-113.84482359, -114.41088165, -114.63386688, -115.92829006,
-117.52597227, -114.49770514, -114.46881502, -76.26871272,
-115.36487081, -160.01242472, -110.6429636, -77.47722955,
-80.24672646, -85.90422427, -94.92075147, -102.44309541,
-106.23741455, -111.56110193, -115.13402727, -48.64043046,
-60.86151946, -66.52137871, -110.04628212, -75.27694696,
-78.87041369, -88.08700161, -90.18844188, -93.65776393,
-92.58976279, -107.31364843, -115.04064471, -125.98500718,
-75.9341032, -39.45970018, -14.74007542, -23.16835763])
test_ry0 = np.array([
5.38783354, 32.4020918, 0., 9.61130904,
6.44049545, 20.09660033, 17.15326613, 37.33355718,
32.13984847, 30.52375962, 48.36955032, 46.80314854,
45.81889319, 59.12136236, 70.83373993, 0.,
0., 0., 0., 0.82164117,
3.77918116, 10.05956987, 15.25300766, 12.0392273,
11.14109933, 4.95094623, 15.40879915, 18.26971567,
26.20071419, 32.10315546, 17.82930838, 16.47901983,
37.63130193, 34.89271046, 36.93871646, 41.37810916,
50.20857205, 49.88348379, 53.00427791, 56.19450179,
55.00318781, 52.05668021, 63.5742463, 75.23991598,
76.73743813, 69.5633335, 72.0826857, 71.37320068,
63.51178836, 5.38783354, 4.91724596, 64.6247091,
44.16641261, 0.79991336, 37.17814456, 0.,
26.64516892, 25.2901784, 30.87900047, 42.64471355,
0., 4.46617283, 0., 70.11682926,
54.09947445, 44.11969128, 0., 36.27214079,
0., 38.18365743, 37.69324975, 37.69324975,
63.38593626, 31.95985109, 0., 154.11892278,
46.64285745, 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 15.76388487, 0., 9.33917446,
3.08664273, 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 4.77794806, 17.69115659,
0., 0., 20.17492433, 1.11830182,
0., 0., 0., 0.,
3.58647845, 0.46532899, 11.2919028, 1.6635569,
1.97425251, 0., 0., 0.,
0., 77.92575377, 73.39710471, 68.56706103,
63.54889567, 59.58494138, 54.62777528, 50.6026715,
59.61994802, 51.46197518, 65.7385149, 61.02147746,
57.23577546, 64.69948606, 61.52738171, 57.19564204,
49.34737949, 57.7005733, 61.24113602, 50.81292419,
53.04327558, 70.50571919, 66.89431913, 61.93293686,
63.95088168, 61.69626833, 58.55290391, 51.32778327,
54.3927127, 54.84479095, 65.04953504, 64.65221582,
31.95985109, 58.48352003, 52.10343269, 88.55095607,
63.56398477, 65.81489046, 56.97061016, 43.22012866,
37.05903154, 44.9197184, 37.63547806, 34.54073112,
24.91252804, 43.85603511, 104.24271216, 106.54672867,
100.25896283, 101.69591788, 88.22817597, 91.26318052,
77.24221603, 99.89093129, 73.86954084, 71.41901185,
94.92990813, 99.23743511, 107.91756944, 115.88637645,
105.82795138, 131.33670356, 137.14308555, 144.9987485,
133.01516376, 150.34316435, 160.68282361, 117.17751011,
154.11892278, 52.87427275, 89.6257514, 40.8453683,
121.11057005, 158.61579065, 30.67888078, 103.50740842,
100.77412349, 104.07620713, 78.9431475, 89.30051368,
92.43855998, 70.06512676, 107.15463315, 102.65326198,
112.33058622, 82.19476634, 87.57760872, 153.75929106,
160.55658764, 105.97913971, 77.69812572, 87.13285248,
104.55104982, 101.41786275, 68.92193392, 46.49788654,
32.0326699, 3.80278787, 25.14287639, 89.6257514,
84.39813309, 40.8453683, 64.6247091, 84.19418317,
87.06845748, 90.61543602, 89.45725966, 87.65788171,
88.16667274, 85.73221021, 85.81702431, 86.36958842,
86.92965411, 83.87627959, 84.67250815, 85.02871339,
81.30217949, 82.00166833, 80.95567535, 79.72940282,
76.94041117, 74.15932662, 72.58296373, 95.24725733,
90.83339137, 77.0951865, 97.10129692, 71.60389476,
92.49353057, 88.16446736, 84.80001222, 76.89046231,
99.93243461, 100.9942771, 101.31862755, 98.37818371,
80.61034346, 93.61235363, 83.46840575, 89.00485915,
95.30577334, 95.23683984, 93.03317965, 94.37882485,
104.55109142, 104.93660016, 77.70875494, 87.54812917,
88.21438842, 92.90184589, 92.78475848, 83.07370447,
91.04478743, 84.13122931, 94.34156384, 116.14580381,
0., 74.60228349, 62.05277372, 75.26960919,
73.05255319, 69.36721657, 70.69339281, 63.60858937,
79.3945774, 41.33668124, 45.83428785, 56.48895409,
44.27601238, 47.50182027, 16.56678743, 15.30399771,
32.28456656, 27.77220427, 4.53784286, 7.56226086,
11.54803229, 3.27669605, 18.1877873, 21.032248,
12.40326116, 28.80177485, 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.,
46.64285745, 0., 68.82644897, 0.,
46.49788654, 0., 2.41780516, 0.,
75.36373283, 46.11687074, 37.89624258, 45.60453732,
38.89268605, 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 0., 0.,
0., 0., 3.80278787, 0.,
0., 0., 0., 0.,
0., 60.30287357, 71.49824989, 9.02262176,
46.36088598, 88.35995182, 56.65793884, 71.37390848,
69.97820268, 70.54426073, 70.76724596, 72.06166914,
73.65935135, 70.63108422, 70.6021941, 32.4020918,
71.49824989, 116.14580381, 66.77634268, 33.61060864,
36.38010555, 42.03760335, 51.05413055, 58.57647449,
62.37079364, 67.69448101, 71.26740635, 4.77380954,
16.99489854, 22.65475779, 66.1796612, 31.41032604,
35.00379277, 44.22038069, 46.32182096, 49.79114301,
48.72314188, 63.44702751, 71.1740238, 82.11838626,
32.06748228, 0., 0., 0.])
dist_types = ['repi', 'rhypo', 'rjb', 'rrup', 'rx', 'ry', 'ry0', 'U', 'T']
dists = get_distance(dist_types, slat, slon, sdep, source)
np.testing.assert_allclose(
nga_repi, dists['repi'], rtol=0, atol=2)
np.testing.assert_allclose(
nga_rhypo, dists['rhypo'], rtol=0, atol=2)
np.testing.assert_allclose(
nga_rjb, dists['rjb'], rtol=0, atol=2)
np.testing.assert_allclose(
nga_rrup, dists['rrup'], rtol=0, atol=2)
np.testing.assert_allclose(
nga_rx, dists['rx'], rtol=0, atol=2)
np.testing.assert_allclose(
test_ry, dists['ry'], rtol=0, atol=2)
np.testing.assert_allclose(
test_ry0, dists['ry0'], rtol=0, atol=2)
np.testing.assert_allclose(
nga_U, dists['U'], rtol=0, atol=6)
np.testing.assert_allclose(
nga_T, dists['T'], rtol=0, atol=2)
