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 plot_restored_locations(slips, heaves):
"""Plot the map-view location of each horizon's restored position."""
# Prepend the present-day location of 0,0 for plotting...
slips = [(0, 0)] + slips
heaves = [(0, 0, 0)] + heaves
slip_x, slip_y = np.array(slips).T
heave_x, heave_y, heave_z = np.array(heaves).T
fig, ax = plt.subplots()
ax.plot(slip_x, slip_y, 'bo-')
ax.plot(heave_x, heave_y, 'go-')
utilities.plot_plate_motion(time=2e5, xy=slips[3])
plt.axis('equal')
return fig, ax
def plot_restored_locations(slips, heaves):
"""Plot the map-view location of each horizon's restored position."""
# Prepend the present-day location of 0,0 for plotting...
slips = [(0,0)] + slips
heaves = [(0,0,0)] + heaves
slip_x, slip_y = np.array(slips).T
heave_x, heave_y, heave_z = np.array(heaves).T
fig, ax = plt.subplots()
ax.plot(slip_x, slip_y, 'bo-')
ax.plot(heave_x, heave_y, 'go-')
utilities.plot_plate_motion(time=2e5, xy=slips[3])
plt.axis('equal')
return fig, ax
models = [[0, 0]]
i = 0
for hor in data.horizons[::-1]:
print hor.name
# Downsample horizon for faster solution...
xyz = data.to_xyz(hor)[::50,:]
xyz = data.to_world(xyz)
# Move this horizon to the last horizon's best fit offset.
# Following the path of all previous horizons...
for model in models:
dx, dy = model
xyz = inclined_shear(fault, xyz, (dx,dy), data.alpha)
model = invert_slip(fault, xyz, data.alpha, guess=(0,0))
models.append(model)
i += 1
models = np.array(models)
movement = models[:,:2].cumsum(axis=0)
x, y = movement.T
plt.plot(x, y, marker='o')
utilities.plot_plate_motion(time=3e5)
plt.axis('equal')
plt.show()
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-')
utilities.plot_plate_motion(time=2e5, xy=slips[3])
plt.axis('equal')
plt.show()
models = [[0, 0]]
i = 0
for hor in data.horizons[::-1]:
print hor.name
# Downsample horizon for faster solution...
xyz = data.to_xyz(hor)[::50, :]
xyz = data.to_world(xyz)
# Move this horizon to the last horizon's best fit offset.
# Following the path of all previous horizons...
for model in models:
dx, dy = model
xyz = inclined_shear(fault, xyz, (dx, dy), data.alpha)
model = invert_slip(fault, xyz, data.alpha, guess=(0, 0))
models.append(model)
i += 1
models = np.array(models)
movement = models[:, :2].cumsum(axis=0)
x, y = movement.T
plt.plot(x, y, marker='o')
utilities.plot_plate_motion(time=3e5)
plt.axis('equal')
plt.show()
