def test_get_area1(self):
pntsa = npoints_towards(lon=0.32,
lat=0.0,
depth=0.0,
azimuth=45,
hdist=10.0,
vdist=0.0,
npoints=2)
pntsb = npoints_towards(lon=pntsa[0][1],
lat=pntsa[1][1],
depth=pntsa[2][1],
azimuth=45 + 90,
hdist=10.0,
vdist=10.0,
npoints=2)
pntsc = npoints_towards(lon=0.32,
lat=0.0,
depth=0.0,
azimuth=45 + 90,
hdist=10.0,
vdist=10.0,
npoints=2)
tmp = Point(pntsc[0][1], pntsc[1][1], pntsc[2][1])
prf3 = Line([Point(0.32, 0, 0), tmp])
tmp1 = Point(pntsa[0][1], pntsa[1][1], pntsa[2][1])
tmp2 = Point(pntsb[0][1], pntsb[1][1], pntsb[2][1])
prf4 = Line([tmp1, tmp2])
sfcb = KiteSurface.from_profiles([prf3, prf4], 0.2, 0.2)
computed = sfcb.get_area()
expected = 10.0 * 14.14
msg = 'Multi fault surface: area is wrong'
aae(expected, computed, decimal=-1, err_msg=msg)
def test_zero_distance(self):
lon, lat, depth, azimuth = 12, 34, 56, 78
lons, lats, depths = geodetic.npoints_towards(
lon, lat, depth, azimuth, hdist=0, vdist=0, npoints=5
)
expected_lons = [lon] * 5
expected_lats = [lat] * 5
expected_depths = [depth] * 5
assert_aeq(lons, expected_lons)
assert_aeq(lats, expected_lats)
assert_aeq(depths, expected_depths)
def test_zero_distance(self):
lon, lat, depth, azimuth = 12, 34, 56, 78
lons, lats, depths = geodetic.npoints_towards(
lon, lat, depth, azimuth, hdist=0, vdist=0, npoints=5
)
expected_lons = [lon] * 5
expected_lats = [lat] * 5
expected_depths = [depth] * 5
self.assertTrue(numpy.allclose(lons, expected_lons))
self.assertTrue(numpy.allclose(lats, expected_lats))
self.assertTrue(numpy.allclose(depths, expected_depths))
def test_zero_distance(self):
lon, lat, depth, azimuth = 12, 34, 56, 78
lons, lats, depths = geodetic.npoints_towards(
lon, lat, depth, azimuth, hdist=0, vdist=0, npoints=5
)
expected_lons = [lon] * 5
expected_lats = [lat] * 5
expected_depths = [depth] * 5
assert_aeq(lons, expected_lons)
assert_aeq(lats, expected_lats)
assert_aeq(depths, expected_depths)
def setUp(self):
# First surface - Almost vertical dipping to south
prf1 = Line([Point(0, 0, 0), Point(0, -0.00001, 20.)])
prf2 = Line([Point(0.15, 0, 0), Point(0.15, -0.00001, 20.)])
prf3 = Line([Point(0.3, 0, 0), Point(0.3, -0.00001, 20.)])
sfca = KiteSurface.from_profiles([prf1, prf2, prf3], 1., 1.)
# Second surface - Strike to NE and dip to SE
pntsa = npoints_towards(lon=0.32,
lat=0.0,
depth=0.0,
azimuth=45,
hdist=10.0,
vdist=0.0,
npoints=2)
pntsb = npoints_towards(lon=pntsa[0][1],
lat=pntsa[1][1],
depth=pntsa[2][1],
azimuth=45 + 90,
hdist=10.0,
vdist=10.0,
npoints=2)
pntsc = npoints_towards(lon=0.32,
lat=0.0,
depth=0.0,
azimuth=45 + 90,
hdist=10.0,
vdist=10.0,
npoints=2)
tmp = Point(pntsc[0][1], pntsc[1][1], pntsc[2][1])
prf3 = Line([Point(0.32, 0, 0), tmp])
tmp1 = Point(pntsa[0][1], pntsa[1][1], pntsa[2][1])
tmp2 = Point(pntsb[0][1], pntsb[1][1], pntsb[2][1])
prf4 = Line([tmp1, tmp2])
sfcb = KiteSurface.from_profiles([prf3, prf4], 0.2, 0.2)
# Create surface and mesh needed for the test
self.msrf = MultiSurface([sfca, sfcb])
self.coo = np.array([[-0.1, 0.0], [0.0, 0.1]])
self.mesh = Mesh(self.coo[:, 0], self.coo[:, 1])
def compute_profiles(self, bffer):
"""
Compute the profile for each cross-section using the slab mesh.
:param bffer:
Buffer distance [km] from the plane of the cross-section used to
find the points.
"""
hspacing = 5.0
slab_points = copy.copy(self.points)
# Set values in the range [-180, 180]
idx = numpy.nonzero(self.points[:, 0] > 180)
if len(idx[0]):
slab_points[idx[0], 0] = slab_points[idx[0], 0] - 360.
# Loop over the cross-sections
self.profiles = {}
for ics, cs in enumerate(self.cross_sections):
pnts = copy.copy(slab_points)
# Get min and max longitude and latitude values
minlo, maxlo, minla, maxla, qual = cs.get_mm()
# Find the nodes of the grid within a certain distance from the
# plane of the cross-section
if qual == 0:
minlo, maxlo, minla, maxla, qual = cs.get_mm(2.0)
idxslb, dsts = cs.get_grd_nodes_within_buffer(
pnts[:, 0], pnts[:, 1], bffer, minlo, maxlo, minla, maxla)
if qual == 1:
idxslb, dsts = cs.get_grd_nodes_within_buffer_idl(
pnts[:, 0], pnts[:, 1], bffer, minlo, maxlo, minla, maxla)
# Check if the array with cross-section data is not empty
if idxslb is None:
continue
# Points
num = numpy.ceil(cs.length[0]/hspacing).astype(int)
psec = npoints_towards(cs.olo, cs.ola, 0.0, cs.strike[0],
cs.length[0], 0., num)
p = pnts[idxslb, :]
interp = LinearNDInterpolator(p[:, 0:2], p[:, 2])
z = interp(psec[0], psec[1])
iii = numpy.isfinite(z)
pro = numpy.concatenate((numpy.expand_dims(psec[0][iii], axis=1),
numpy.expand_dims(psec[1][iii], axis=1),
numpy.expand_dims(z[iii], axis=1)),
axis=1)
pro[:, 2] *= -1
self.profiles['{:03d}'.format(ics)] = pro
def test_input_as_int(self):
lons, lats, depths = geodetic.npoints_towards(
lon=0, lat=0, depth=0, azimuth=0,
hdist=0, vdist=5, npoints=7
)
expected_lons = [0, 0, 0, 0, 0, 0, 0]
expected_lats = [0, 0, 0, 0, 0, 0, 0]
expected_depths = [0, 0.8333333, 1.6666667, 2.5, 3.3333333, 4.1666667, 5]
numpy.testing.assert_almost_equal(lons, expected_lons)
numpy.testing.assert_almost_equal(lats, expected_lats)
numpy.testing.assert_almost_equal(depths, expected_depths)
self.assertEqual(lons[0], 0)
self.assertEqual(lats[0], 0)
self.assertEqual(depths[0], 0)
def test_input_as_int(self):
lons, lats, depths = geodetic.npoints_towards(
lon=0, lat=0, depth=0, azimuth=0,
hdist=0, vdist=5, npoints=7
)
expected_lons = [0, 0, 0, 0, 0, 0, 0]
expected_lats = [0, 0, 0, 0, 0, 0, 0]
expected_depths = [0, 0.8333333, 1.6666667, 2.5, 3.3333333,
4.1666667, 5]
numpy.testing.assert_almost_equal(lons, expected_lons)
numpy.testing.assert_almost_equal(lats, expected_lats)
numpy.testing.assert_almost_equal(depths, expected_depths)
self.assertEqual(lons[0], 0)
self.assertEqual(lats[0], 0)
self.assertEqual(depths[0], 0)
def test(self):
lons, lats, depths = geodetic.npoints_towards(
lon=-30.5, lat=23.6, depth=55, azimuth=-100.5,
hdist=400, vdist=-40, npoints=5
)
expected_lons = [-30.5, -31.46375358, -32.42503446,
-33.3837849, -34.33995063]
expected_lats = [23.6, 23.43314083, 23.26038177,
23.08178673, 22.8974212]
expected_depths = [55, 45, 35, 25, 15]
self.assertTrue(numpy.allclose(lons, expected_lons))
self.assertTrue(numpy.allclose(lats, expected_lats))
self.assertTrue(numpy.allclose(depths, expected_depths))
# the first point should be exactly the same
# as the original starting point
self.assertEqual(lons[0], -30.5)
self.assertEqual(lats[0], 23.6)
self.assertEqual(depths[0], 55)
def test_topo(self):
lons, lats, depths = geodetic.npoints_towards(
lon=-30.5, lat=23.6, depth=2, azimuth=-100.5,
hdist=400, vdist=-4, npoints=5
)
expected_lons = [-30.5, -31.46375358, -32.42503446,
-33.3837849, -34.33995063]
expected_lats = [23.6, 23.43314083, 23.26038177,
23.08178673, 22.8974212]
expected_depths = [2, 1, 0, -1, -2]
assert_aeq(lons, expected_lons)
assert_aeq(lats, expected_lats)
assert_aeq(depths, expected_depths)
# the first point should be exactly the same
# as the original starting point
self.assertEqual(lons[0], -30.5)
self.assertEqual(lats[0], 23.6)
self.assertEqual(depths[0], 2)
def test_topo(self):
lons, lats, depths = geodetic.npoints_towards(
lon=-30.5, lat=23.6, depth=2, azimuth=-100.5,
hdist=400, vdist=-4, npoints=5
)
expected_lons = [-30.5, -31.46375358, -32.42503446,
-33.3837849, -34.33995063]
expected_lats = [23.6, 23.43314083, 23.26038177,
23.08178673, 22.8974212]
expected_depths = [2, 1, 0, -1, -2]
assert_aeq(lons, expected_lons)
assert_aeq(lats, expected_lats)
assert_aeq(depths, expected_depths)
# the first point should be exactly the same
# as the original starting point
self.assertEqual(lons[0], -30.5)
self.assertEqual(lats[0], 23.6)
self.assertEqual(depths[0], 2)
def _resample_profile(line, sampling_dist):
# TODO split this function into smaller components.
"""
:parameter line:
An instance of :class:`openquake.hazardlib.geo.line.Line`
:parameter sampling_dist:
A scalar definining the distance [km] used to sample the profile
:returns:
An instance of :class:`openquake.hazardlib.geo.line.Line`
"""
lo = [pnt.longitude for pnt in line.points]
la = [pnt.latitude for pnt in line.points]
de = [pnt.depth for pnt in line.points]
# Set projection
g = Geod(ellps='WGS84')
# Add a tolerance length to the last point of the profile
# check that final portion of the profile is not vertical
if abs(lo[-2] - lo[-1]) > 1e-5 and abs(la[-2] - la[-1]) > 1e-5:
az12, _, odist = g.inv(lo[-2], la[-2], lo[-1], la[-1])
odist /= 1e3
slope = np.arctan((de[-1] - de[-2]) / odist)
hdist = TOL * sampling_dist * np.cos(slope)
vdist = TOL * sampling_dist * np.sin(slope)
endlon, endlat, _ = g.fwd(lo[-1], la[-1], az12, hdist * 1e3)
lo[-1] = endlon
la[-1] = endlat
de[-1] = de[-1] + vdist
az12, _, odist = g.inv(lo[-2], la[-2], lo[-1], la[-1])
# Checking
odist /= 1e3
slopec = np.arctan((de[-1] - de[-2]) / odist)
assert abs(slope - slopec) < 1e-3
else:
de[-1] = de[-1] + TOL * sampling_dist
# Initialise the cumulated distance
cdist = 0.
# Get the azimuth of the profile
azim = azimuth(lo[0], la[0], lo[-1], la[-1])
# Initialise the list with the resampled nodes
idx = 0
resampled_cs = [Point(lo[idx], la[idx], de[idx])]
# Set the starting point
slo = lo[idx]
sla = la[idx]
sde = de[idx]
# Resampling
while 1:
# Check loop exit condition
if idx > len(lo) - 2:
break
# Compute the distance between the starting point and the next point
# on the profile
segment_len = distance(slo, sla, sde, lo[idx + 1], la[idx + 1],
de[idx + 1])
# Search for the point
if cdist + segment_len > sampling_dist:
# This is the lenght of the last segment-fraction needed to
# obtain the sampling distance
delta = sampling_dist - cdist
# Compute the slope of the last segment and its horizontal length.
# We need to manage the case of a vertical segment TODO
segment_hlen = distance(slo, sla, 0., lo[idx + 1], la[idx + 1], 0.)
if segment_hlen > 1e-5:
segment_slope = np.arctan((de[idx + 1] - sde) / segment_hlen)
else:
segment_slope = 90.
# Horizontal and vertical lenght of delta
delta_v = delta * np.sin(segment_slope)
delta_h = delta * np.cos(segment_slope)
# Add a new point to the cross section
pnts = npoints_towards(slo, sla, sde, azim, delta_h, delta_v, 2)
# Update the starting point
slo = pnts[0][-1]
sla = pnts[1][-1]
sde = pnts[2][-1]
resampled_cs.append(Point(slo, sla, sde))
# Reset the cumulative distance
cdist = 0.
else:
cdist += segment_len
idx += 1
slo = lo[idx]
sla = la[idx]
sde = de[idx]
# Check the distances along the profile
coo = [[pnt.longitude, pnt.latitude, pnt.depth] for pnt in resampled_cs]
coo = np.array(coo)
for i in range(0, coo.shape[0] - 1):
dst = distance(coo[i, 0], coo[i, 1], coo[i, 2], coo[i + 1, 0],
coo[i + 1, 1], coo[i + 1, 2])
if abs(dst - sampling_dist) > 0.1 * sampling_dist:
raise ValueError('Wrong distance between points along the profile')
return Line(resampled_cs)
def _resample_edge_with_direction(edge,
sampling_dist,
reference_idx,
direct=+1):
"""
:param edge:
:param sampling_dist:
:param reference_idx:
:param direct:
"""
#
# checking that the increment is either 1 or -1
assert abs(direct) == 1
#
# create three lists: one with longitude, one with latitude and one with
# depth
lo = [pnt.longitude for pnt in edge.points]
la = [pnt.latitude for pnt in edge.points]
de = [pnt.depth for pnt in edge.points]
#
# initialise the variable used to store the cumulated distance
cdist = 0.
#
# initialise the list with the resampled nodes
idx = reference_idx
resampled_cs = [Point(lo[idx], la[idx], de[idx])]
#
# set the starting point
slo = lo[idx]
sla = la[idx]
sde = de[idx]
#
# get the azimuth of the first segment on the edge in the given direction
azim = azimuth(lo[idx], la[idx], lo[idx + direct], la[idx + direct])
#
# resampling
old_dst = 1.e10
while 1:
#
# this is a sanity check
assert idx <= len(lo) - 1
#
# check loop exit condition
if direct > 0 and idx > len(lo) - 1:
break
if direct < 0 and idx < 1:
break
#
# compute the distance between the starting point and the next point
# on the profile
segment_len = distance(slo, sla, sde, lo[idx + direct],
la[idx + direct], de[idx + direct])
#
# search for the point
if cdist + segment_len > sampling_dist:
#
# check
if segment_len > old_dst:
print(segment_len, '>', old_dst)
raise ValueError('The segment length is increasing')
else:
old_dst = segment_len
#
# this is the lenght of the last segment-fraction needed to
# obtain the sampling distance
delta = sampling_dist - cdist
#
# compute the slope of the last segment and its horizontal length.
# we need to manage the case of a vertical segment TODO
segment_hlen = distance(slo, sla, 0., lo[idx + direct],
la[idx + direct], 0.)
segment_slope = np.arctan((de[idx + direct] - sde) / segment_hlen)
#
# horizontal and vertical lenght of delta
delta_v = delta * np.sin(segment_slope)
delta_h = delta * np.cos(segment_slope)
#
# add a new point to the cross section
pnts = npoints_towards(slo, sla, sde, azim, delta_h, delta_v, 2)
#
# update the starting point
slo = pnts[0][-1]
sla = pnts[1][-1]
sde = pnts[2][-1]
#
# checking distance between the reference point and latest point
# included in the resampled section
pnt = resampled_cs[-1]
checkd = distance(slo, sla, sde, pnt.longitude, pnt.latitude,
pnt.depth)
# >>> TOLERANCE
if (cdist < 1e-2
and abs(checkd - sampling_dist) > 0.05 * sampling_dist):
print(checkd, sampling_dist)
msg = 'Segment distance different than sampling dst'
raise ValueError(msg)
#
# updating the resample cross-section
resampled_cs.append(Point(slo, sla, sde))
#
#
tot = distance(lo[idx], la[idx], de[idx], lo[idx + direct],
la[idx + direct], de[idx + direct])
downd = distance(slo, sla, sde, lo[idx], la[idx], de[idx])
upd = distance(slo, sla, sde, lo[idx + direct], la[idx + direct],
de[idx + direct])
#
# >>> TOLERANCE
if abs(tot - (downd + upd)) > tot * 0.05:
print(' upd, downd, tot', upd, downd, tot)
print(abs(tot - (downd + upd)))
raise ValueError('Distances are not matching')
#
# reset the cumulative distance
cdist = 0.
else:
# print('aa', cdist, segment_len, sampling_dist)
# print(' ', idx, len(lo)-1, direct)
#
#
old_dst = 1.e10
cdist += segment_len
idx += direct
slo = lo[idx]
sla = la[idx]
sde = de[idx]
#
# get the azimuth of the profile
if idx < len(lo) - 1:
azim = azimuth(lo[idx], la[idx], lo[idx + direct],
la[idx + direct])
else:
break
#
#
return resampled_cs
def rsmpl_unsure(ix, iy, sampling_dist):
direct = 1
idx = 0
#
# create three lists: one with longitude, one with latitude and one with
# depth
lo = list(ix)
la = list(iy)
de = list(numpy.zeros_like(ix))
#
# initialise the variable used to store the cumulated distance
cdist = 0.
#
# set the starting point
slo = lo[idx]
sla = la[idx]
sde = de[idx]
#
# get the azimuth of the first segment on the edge in the given direction
azim = azimuth(lo[idx], la[idx], lo[idx + direct], la[idx + direct])
#
# initialise the list with the resampled nodes
resampled_cs = [[lo[idx], la[idx], azim]]
#
# resampling
while 1:
#
# this is a sanity check
assert idx <= len(lo) - 1
#
# check loop exit condition
if direct > 0 and idx > len(lo) - 1:
break
#
# compute the distance between the starting point and the next point
# on the profile
segment_len = distance(slo, sla, sde, lo[idx + direct],
la[idx + direct], de[idx + direct])
#
# search for the point
if cdist + segment_len > sampling_dist:
#
# this is the lenght of the last segment-fraction needed to
# obtain the sampling distance
delta = sampling_dist - cdist
#
# add a new point to the cross section
pnts = npoints_towards(slo, sla, sde, azim, delta, 0., 2)
#
# update the starting point
slo = pnts[0][-1]
sla = pnts[1][-1]
sde = pnts[2][-1]
resampled_cs.append([slo, sla, azim])
#
# reset the cumulative distance
cdist = 0.
else:
cdist += segment_len
idx += direct
slo = lo[idx]
sla = la[idx]
sde = de[idx]
#
# get the azimuth of the profile
if idx < len(lo) - 1:
azim = azimuth(lo[idx], la[idx], lo[idx + direct],
la[idx + direct])
else:
break
# code.interact(local=locals())
return numpy.array(resampled_cs)
def _resample_profile(line, sampling_dist):
"""
:parameter line:
An instance of :class:`openquake.hazardlib.geo.line.Line`
:parameter sampling_dist:
A scalar definining the distance used to sample the profile
:returns:
An instance of :class:`openquake.hazardlib.geo.line.Line`
"""
lo = [pnt.longitude for pnt in line.points]
la = [pnt.latitude for pnt in line.points]
de = [pnt.depth for pnt in line.points]
#
# initialise the cumulated distance
cdist = 0.
#
# get the azimuth of the profile
azim = azimuth(lo[0], la[0], lo[-1], la[-1])
#
# initialise the list with the resampled nodes
idx = 0
resampled_cs = [Point(lo[idx], la[idx], de[idx])]
#
# set the starting point
slo = lo[idx]
sla = la[idx]
sde = de[idx]
#
# resampling
while 1:
#
# check loop exit condition
if idx > len(lo) - 2:
break
#
# compute the distance between the starting point and the next point
# on the profile
segment_len = distance(slo, sla, sde, lo[idx + 1], la[idx + 1],
de[idx + 1])
#
# search for the point
if cdist + segment_len > sampling_dist:
#
# this is the lenght of the last segment-fraction needed to
# obtain the sampling distance
delta = sampling_dist - cdist
#
# compute the slope of the last segment and its horizontal length.
# We need to manage the case of a vertical segment TODO
segment_hlen = distance(slo, sla, 0., lo[idx + 1], la[idx + 1], 0.)
segment_slope = np.arctan((de[idx + 1] - sde) / segment_hlen)
#
# horizontal and vertical lenght of delta
delta_v = delta * np.sin(segment_slope)
delta_h = delta * np.cos(segment_slope)
#
# add a new point to the cross section
pnts = npoints_towards(slo, sla, sde, azim, delta_h, delta_v, 2)
#
# update the starting point
slo = pnts[0][-1]
sla = pnts[1][-1]
sde = pnts[2][-1]
resampled_cs.append(Point(slo, sla, sde))
#
# reset the cumulative distance
cdist = 0.
else:
cdist += segment_len
idx += 1
slo = lo[idx]
sla = la[idx]
sde = de[idx]
line = Line(resampled_cs)
return line
