def main():
fig, ax = plt.subplots()
ax.set_xlabel('Eastward Slip (m)')
ax.set_ylabel('Northward Slip (m)')
offsets = [[0, 0]]
heaves = [[0,0,0]]
for hor, name in zip(data.horizons[::-1], data.gulick_names[::-1]):
results = get_result(hor.name)
discarded = 200 - results.shape[0]
print 'Discarded {} points from {}'.format(discarded, hor.name)
# Plot covariance ellipse...
dx, dy, slip = plot(ax, results, '# ' + name)
offsets.append([dx, dy])
heaves.append(utilities.calculate_heave([dx, dy], hor))
# Plot plate motion over 200kyr
utilities.plot_plate_motion(xy=offsets[3], time=2e5)
# Plot lines connecting the horizons...
ax.plot(*zip(*offsets), marker='o', color='darkred')
# Plot heaves...
heaves = np.array(heaves)
ax.plot(*heaves[:,:2].T, marker='o', color='green')
# Set aspect ratio of plot to 1 so that azimuths are properly represented
ax.axis('equal')
plt.show()
def main():
fig, ax = plt.subplots()
ax.set_xlabel('Eastward Slip (m)')
ax.set_ylabel('Northward Slip (m)')
offsets = [[0, 0]]
heaves = [[0, 0, 0]]
for hor, name in zip(data.horizons[::-1], data.gulick_names[::-1]):
results = get_result(hor.name)
discarded = 200 - results.shape[0]
print 'Discarded {} points from {}'.format(discarded, hor.name)
# Plot covariance ellipse...
dx, dy, slip = plot(ax, results, '# ' + name)
offsets.append([dx, dy])
heaves.append(utilities.calculate_heave([dx, dy], hor))
# Plot plate motion over 200kyr
utilities.plot_plate_motion(xy=offsets[3], time=2e5)
# Plot lines connecting the horizons...
ax.plot(*zip(*offsets), marker='o', color='darkred')
# Plot heaves...
heaves = np.array(heaves)
ax.plot(*heaves[:, :2].T, marker='o', color='green')
# Set aspect ratio of plot to 1 so that azimuths are properly represented
ax.axis('equal')
plt.show()
def restore_horizons(func=invert_slip):
"""
Restore each of the uplifted horizons individually.
"func" just allows overriding of the specific inversion (e.g. see
"invert_slip_fixed_azimuth.py") without code duplication.
"""
# Note that we start each horizon at zero offset and restore independently
guess = (0, 0)
variances, planar_variances = [], []
slips, heaves = [], []
for hor in data.horizons[::-1]:
hor_xyz = data.world_xyz(hor)
# Downsample the horizon for faster runtime
# (No need to include millions of points along the horizon's surface)
hor_xyz = hor_xyz[::50]
# Invert for the slip along the fault needed to restore the horizon
# to horizontal.
slip, metric = func(data.fault_xyz,
hor_xyz,
alpha=data.alpha,
guess=guess,
overlap_thresh=1,
return_metric=True)
heave = utilities.calculate_heave(slip, hor)
variances.append(metric)
planar_var = planar_variance(hor_xyz)
planar_variances.append(planar_var)
slips.append(slip)
heaves.append(heave)
# Note: We're plotting "metric / planar_var" to allow a direct
# comparison of the quality of the fit between different horizons.
print 'Restoring', hor.name
print ' Roughness (lower is better):', metric / planar_var
return slips, heaves, variances, planar_variances
def restore_horizons(func=invert_slip):
"""
Restore each of the uplifted horizons individually.
"func" just allows overriding of the specific inversion (e.g. see
"invert_slip_fixed_azimuth.py") without code duplication.
"""
# Note that we start each horizon at zero offset and restore independently
guess = (0,0)
variances, planar_variances = [], []
slips, heaves = [], []
for hor in data.horizons[::-1]:
hor_xyz = data.world_xyz(hor)
# Downsample the horizon for faster runtime
# (No need to include millions of points along the horizon's surface)
hor_xyz = hor_xyz[::50]
# Invert for the slip along the fault needed to restore the horizon
# to horizontal.
slip, metric = func(data.fault_xyz, hor_xyz, alpha=data.alpha,
guess=guess, overlap_thresh=1, return_metric=True)
heave = utilities.calculate_heave(slip, hor)
variances.append(metric)
planar_var = planar_variance(hor_xyz)
planar_variances.append(planar_var)
slips.append(slip)
heaves.append(heave)
# Note: We're plotting "metric / planar_var" to allow a direct
# comparison of the quality of the fit between different horizons.
print 'Restoring', hor.name
print ' Roughness (lower is better):', metric / planar_var
return slips, heaves, variances, planar_variances
slips = [(0,0)]
guess = (0,0)
heaves = [(0,0,0)]
planar_variances = []
variances = []
for i, hor in enumerate(data.horizons[::-1]):
print hor.name
xyz = data.to_xyz(hor)[::50]
xyz = data.to_world(xyz)
slip, metric = invert_slip(fault, xyz, alpha=data.alpha, guess=guess,
overlap_thresh=1, return_metric=True)
heave = utilities.calculate_heave(slip, hor)
variances.append(metric)
planar_var = planar_variance(xyz)
planar_variances.append(planar_var)
print metric / planar_var
slips.append(slip)
heaves.append(heave)
x, y = np.array(slips).T
plt.plot(x, y, 'bo-')
x, y, z = np.array(heaves).T
plt.plot(x, y, 'go-')
def heave():
results = bootstrap_results()
slip = results.mean(axis=0)
offset = utilities.calculate_heave(slip, data.horizons[0])
return offset[:2]
def heave():
results = bootstrap_results()
slip = results.mean(axis=0)
offset = utilities.calculate_heave(slip, data.horizons[0])
return offset[:2]
