def computeRjb(self, lon, lat, depth, var=False):
"""
Method for computing Joyner-Boore distance.
Args:
lon (array): Numpy array of longitudes.
lat (array): Numpy array of latitudes.
depth (array): Numpy array of depths (km; positive down).
var (bool): Also return variance of prediction. Unused, and
will raise an exception if not False.
Returns:
array: Joyner-Boore distance (km).
"""
if var is True:
raise ValueError('var must be False for EdgeRupture')
# ---------------------------------------------------------------------
# Sort out sites
# ---------------------------------------------------------------------
oldshape = lon.shape
if len(oldshape) == 2:
newshape = (oldshape[0] * oldshape[1], 1)
else:
newshape = (oldshape[0], 1)
x, y, z = latlon2ecef(lat, lon, depth)
x.shape = newshape
y.shape = newshape
z.shape = newshape
sites_ecef = np.hstack((x, y, z))
minrjb = np.ones(newshape, dtype=lon.dtype) * 1e16
quads = self.getQuadrilaterals()
for i in range(len(quads)):
P0, P1, P2, P3 = quads[i]
S0 = copy.deepcopy(P0)
S1 = copy.deepcopy(P1)
S2 = copy.deepcopy(P2)
S3 = copy.deepcopy(P3)
S0.depth = 0.0
S1.depth = 0.0
S2.depth = 0.0
S3.depth = 0.0
squad = [S0, S1, S2, S3]
rjbdist = utils._quad_distance(squad, sites_ecef, horizontal=True)
minrjb = np.minimum(minrjb, rjbdist)
minrjb = minrjb.reshape(oldshape)
return minrjb
def computeRjb(self, lon, lat, depth):
"""
Method for computing Joyner-Boore distance.
Args:
lon (array): Numpy array of longitudes.
lat (array): Numpy array of latitudes.
depth (array): Numpy array of depths (km; positive down).
Returns:
tuple: A tuple of an array of Joyner-Boore distance (km), and None.
"""
# ---------------------------------------------------------------------
# Sort out sites
# ---------------------------------------------------------------------
oldshape = lon.shape
if len(oldshape) == 2:
newshape = (oldshape[0] * oldshape[1], 1)
else:
newshape = (oldshape[0], 1)
x, y, z = latlon2ecef(lat, lon, depth)
x.shape = newshape
y.shape = newshape
z.shape = newshape
sites_ecef = np.hstack((x, y, z))
minrjb = np.ones(newshape, dtype=lon.dtype) * 1e16
quads = self.getQuadrilaterals()
for i in range(len(quads)):
P0, P1, P2, P3 = quads[i]
S0 = copy.deepcopy(P0)
S1 = copy.deepcopy(P1)
S2 = copy.deepcopy(P2)
S3 = copy.deepcopy(P3)
S0.depth = 0.0
S1.depth = 0.0
S2.depth = 0.0
S3.depth = 0.0
squad = [S0, S1, S2, S3]
rjbdist = utils._quad_distance(squad, sites_ecef, horizontal=True)
minrjb = np.minimum(minrjb, rjbdist)
minrjb = minrjb.reshape(oldshape)
return minrjb, None
def computeRrup(self, lon, lat, depth, var=False):
"""
Method for computing rupture distance.
Args:
lon (array): Numpy array of longitudes.
lat (array): Numpy array of latitudes.
depth (array): Numpy array of depths (km; positive down).
var (bool): Also return variance of prediction. Unused, and
will raise an exception if not False.
Returns:
array: Rupture distance (km).
"""
if var is True:
raise ValueError('var must be False for EdgeRupture')
# ---------------------------------------------------------------------
# Sort out sites
# ---------------------------------------------------------------------
oldshape = lon.shape
if len(oldshape) == 2:
newshape = (oldshape[0] * oldshape[1], 1)
else:
newshape = (oldshape[0], 1)
x, y, z = latlon2ecef(lat, lon, depth)
x.shape = newshape
y.shape = newshape
z.shape = newshape
sites_ecef = np.hstack((x, y, z))
minrrup = np.ones(newshape, dtype=lon.dtype) * 1e16
quads = self.getQuadrilaterals()
for i in range(len(quads)):
rrupdist = utils._quad_distance(quads[i], sites_ecef)
minrrup = np.minimum(minrrup, rrupdist)
minrrup = minrrup.reshape(oldshape)
return minrrup
def __computeWrup(self):
"""
Compute the the portion (in km) of the width of the rupture which
ruptures up-dip from the hypocenter to the top of the rupture.
Wrup is the portion (in km) of the width of the rupture which
ruptures up-dip from the hypocenter to the top of the rupture.
* This is ambiguous for ruptures with varible top of rupture (not
allowed in NGA). For now, lets just compute this for the
quad where the hypocenter is located.
* Alternative is to compute max Wrup for the different quads.
"""
nquad = len(self._rup.getQuadrilaterals())
# ---------------------------------------------------------------------
# First find which quad the hypocenter is on
# ---------------------------------------------------------------------
x, y, z = latlon2ecef(self._hyp.latitude, self._hyp.longitude,
self._hyp.depth)
hyp_ecef = np.array([[x, y, z]])
qdist = np.zeros(nquad)
for i in range(0, nquad):
qdist[i] = utils._quad_distance(self._rup.getQuadrilaterals()[i],
hyp_ecef)
ind = int(np.where(qdist == np.min(qdist))[0][0])
# *** check that this doesn't break with more than one quad
q = self._rup.getQuadrilaterals()[ind]
# ---------------------------------------------------------------------
# Compute Wrup on that quad
# ---------------------------------------------------------------------
pp0 = Vector.fromPoint(
geo.point.Point(q[0].longitude, q[0].latitude, q[0].depth))
hyp_ecef = Vector.fromPoint(
geo.point.Point(self._hyp.longitude, self._hyp.latitude,
self._hyp.depth))
hp0 = hyp_ecef - pp0
ddv = utils.get_quad_down_dip_vector(q)
self._Wrup = Vector.dot(ddv, hp0) / 1000
def __computeWrup(self):
"""
Compute the the portion (in km) of the width of the rupture which
ruptures up-dip from the hypocenter to the top of the rupture.
Wrup is the portion (in km) of the width of the rupture which
ruptures up-dip from the hypocenter to the top of the rupture.
* This is ambiguous for ruptures with varible top of rupture (not
allowed in NGA). For now, lets just compute this for the
quad where the hypocenter is located.
* Alternative is to compute max Wrup for the different quads.
"""
nquad = len(self._rup.getQuadrilaterals())
# ---------------------------------------------------------------------
# First find which quad the hypocenter is on
# ---------------------------------------------------------------------
x, y, z = latlon2ecef(
self._hyp.latitude, self._hyp.longitude, self._hyp.depth)
hyp_ecef = np.array([[x, y, z]])
qdist = np.zeros(nquad)
for i in range(0, nquad):
qdist[i] = utils._quad_distance(
self._rup.getQuadrilaterals()[i], hyp_ecef)
ind = int(np.where(qdist == np.min(qdist))[0][0])
# *** check that this doesn't break with more than one quad
q = self._rup.getQuadrilaterals()[ind]
# ---------------------------------------------------------------------
# Compute Wrup on that quad
# ---------------------------------------------------------------------
pp0 = Vector.fromPoint(geo.point.Point(
q[0].longitude, q[0].latitude, q[0].depth))
hyp_ecef = Vector.fromPoint(geo.point.Point(
self._hyp.longitude, self._hyp.latitude, self._hyp.depth))
hp0 = hyp_ecef - pp0
ddv = utils.get_quad_down_dip_vector(q)
self._Wrup = Vector.dot(ddv, hp0) / 1000
def computeRrup(self, lon, lat, depth):
"""
Method for computing rupture distance.
Args:
lon (array): Numpy array of longitudes.
lat (array): Numpy array of latitudes.
depth (array): Numpy array of depths (km; positive down).
Returns:
tuple: A tuple of an array of Rupture distance (km), and None.
"""
# ---------------------------------------------------------------------
# Sort out sites
# ---------------------------------------------------------------------
oldshape = lon.shape
if len(oldshape) == 2:
newshape = (oldshape[0] * oldshape[1], 1)
else:
newshape = (oldshape[0], 1)
x, y, z = latlon2ecef(lat, lon, depth)
x.shape = newshape
y.shape = newshape
z.shape = newshape
sites_ecef = np.hstack((x, y, z))
minrrup = np.ones(newshape, dtype=lon.dtype) * 1e16
quads = self.getQuadrilaterals()
for i in range(len(quads)):
rrupdist = utils._quad_distance(quads[i], sites_ecef)
minrrup = np.minimum(minrrup, rrupdist)
minrrup = minrrup.reshape(oldshape)
return minrrup, None
def getDepthAtPoint(self, lat, lon):
SMALL_DISTANCE = 2e-03 # 2 meters
depth = np.nan
tmp, _ = self.computeRjb(np.array([lon]), np.array([lat]),
np.array([0]))
if tmp > SMALL_DISTANCE:
return depth
i = 0
imin = -1
dmin = 9999999999999999
for quad in self.getQuadrilaterals():
pX = Vector.fromPoint(Point(lon, lat, 0))
points = np.reshape(np.array([pX.x, pX.y, pX.z]), (1, 3))
rjb = utils._quad_distance(quad, points, horizontal=True)
if rjb[0][0] < dmin:
dmin = rjb[0][0]
imin = i
i += 1
quad = self._quadrilaterals[imin]
P0, P1, P2, P3 = quad
# project the quad and the point in question to orthographic defined by
# quad
xmin = np.min([P0.x, P1.x, P2.x, P3.x])
xmax = np.max([P0.x, P1.x, P2.x, P3.x])
ymin = np.min([P0.y, P1.y, P2.y, P3.y])
ymax = np.max([P0.y, P1.y, P2.y, P3.y])
proj = OrthographicProjection(xmin, xmax, ymax, ymin)
# project each vertex of quad (at 0 depth)
s0x, s0y = proj(P0.x, P0.y)
s1x, s1y = proj(P1.x, P1.y)
s2x, s2y = proj(P2.x, P2.y)
s3x, s3y = proj(P3.x, P3.y)
sxx, sxy = proj(lon, lat)
# turn these to vectors
s0 = Vector(s0x, s0y, 0)
s1 = Vector(s1x, s1y, 0)
s3 = Vector(s3x, s3y, 0)
sx = Vector(sxx, sxy, 0)
# Compute vector from s0 to s1
s0s1 = s1 - s0
# Compute the vector from s0 to s3
s0s3 = s3 - s0
# Compute the vector from s0 to sx
s0sx = sx - s0
# cross products
s0normal = s0s3.cross(s0s1)
dd = s0s1.cross(s0normal)
# normalize dd (down dip direction)
ddn = dd.norm()
# dot product
sxdd = ddn.dot(s0sx)
# get width of quad (convert from km to m)
w = utils.get_quad_width(quad) * 1000
# Get weights for top and bottom edge depths
N = utils.get_quad_normal(quad)
V = utils.get_vertical_vector(quad)
dip = np.degrees(np.arccos(Vector.dot(N, V)))
ws = (w * np.cos(np.radians(dip)))
wtt = (ws - sxdd) / ws
wtb = sxdd / ws
# Compute the depth of of the plane at Px:
depth = wtt * P0.z + wtb * P3.z * 1000
return depth