# Show the seeds first to confirm that they are right
fig = mlab.figure()
fig.scene.background = (1, 1, 1)
vis.plot_prism_mesh(model, style='wireframe', xy2ne=True)
plot = vis.plot_prism_mesh(seed_mesh, style='surface', xy2ne=True)
axes = mlab.axes(plot, nb_labels=5, extent=extent, color=(0,0,0))
axes.label_text_property.color = (0,0,0)
axes.title_text_property.color = (0,0,0)
axes.axes.label_format = "%-#.0f"
mlab.outline(color=(0,0,0), extent=extent)
mlab.show()
# Run the inversion
results = gplant.grow(data, mesh, seeds, compactness=10.**(20), power=7,
threshold=1*10**(-4), norm=1, neighbor_type='reduced',
jacobian_file=None, distance_type='radial')
# Unpack the results and calculate the adjustment
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh)
# Pickle results for later
log.info("Pickling results")
output = open('mesh.pickle', 'w')
pickle.dump(mesh, output)
output.close()
seed_file = open("seeds.pickle", 'w')
pickle.dump(seeds, seed_file)
seed_file.close()
nb_labels=5,
extent=extent,
ranges=ranges,
color=(0, 0, 0))
axes.label_text_property.color = (0, 0, 0)
axes.title_text_property.color = (0, 0, 0)
axes.axes.label_format = "%-#.0f"
mlab.outline(color=(0, 0, 0), extent=extent)
mlab.show()
# Run the inversion
results = gplant.grow(data,
mesh,
seeds,
compactness=10.**(5),
power=3,
threshold=10 * 10**(-7),
norm=2,
neighbor_type='reduced',
jacobian_file=None,
distance_type='cell')
# Unpack the results and calculate the adjustment
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh)
corpo = fatiando.mesh.vfilter(mesh, 1, 1000)
# Pickle results for later
log.info("Pickling results")
io.dump('adjusted.txt', adjusted['gz'])
#output = open('mesh.pickle', 'w')
# Show the seeds first to confirm that they are right
fig = mlab.figure()
fig.scene.background = (1, 1, 1)
vis.plot_prism_mesh(model, style='wireframe', xy2ne=True)
plot = vis.plot_prism_mesh(seed_mesh, style='surface', xy2ne=True)
axes = mlab.axes(plot, nb_labels=5, extent=extent, ranges=ranges, color=(0,0,0))
axes.label_text_property.color = (0,0,0)
axes.title_text_property.color = (0,0,0)
axes.axes.label_format = "%-#.0f"
mlab.outline(color=(0,0,0), extent=extent)
mlab.show()
# Run the inversion
results = gplant.grow(data, mesh, seeds, compactness=10.**(5), power=3,
threshold=10*10**(-7), norm=2, neighbor_type='reduced',
jacobian_file=None, distance_type='cell')
# Unpack the results and calculate the adjustment
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh)
corpo = fatiando.mesh.vfilter(mesh, 1, 1000)
# Pickle results for later
log.info("Pickling results")
io.dump('adjusted.txt', adjusted['gz'])
#output = open('mesh.pickle', 'w')
#pickle.dump(mesh, output)
#output.close()
output = open('model.pickle', 'w')
pylab.ylabel('Easting [m]')
pylab.show()
fig = mlab.figure()
fig.scene.background = (1, 1, 1)
fig.scene.camera.yaw(230)
plot = vis.plot_prism_mesh(mesh, opacity=0.4)
plot = vis.plot_prism_mesh(seed_mesh)
axes = mlab.axes(plot, nb_labels=5, extent=[xmin,xmax,ymin,ymax,-zmax,-zmin])
mlab.show()
# Run the inversion
results = gplant.grow(data, mesh, seeds, compactness=10**(5), power=5, norm=1,
threshold=5*10**(-5), jacobian_file=None,
distance_type='radial')
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh, fillNone=False)
log.info("Pickling results")
output = open('mesh.pickle', 'w')
pickle.dump(mesh, output)
output.close()
seed_file = open("seeds.pickle", 'w')
fig.scene.background = (1, 1, 1)
vis.plot_prism_mesh(model, style='wireframe', xy2ne=True)
plot = vis.plot_prism_mesh(seed_mesh, style='surface', xy2ne=True)
axes = mlab.axes(plot, nb_labels=5, extent=extent, color=(0, 0, 0))
axes.label_text_property.color = (0, 0, 0)
axes.title_text_property.color = (0, 0, 0)
axes.axes.label_format = "%-#.0f"
mlab.outline(color=(0, 0, 0), extent=extent)
mlab.show()
# Run the inversion
results = gplant.grow(data,
mesh,
seeds,
compactness=10.**(20),
power=7,
threshold=1 * 10**(-4),
norm=1,
neighbor_type='reduced',
jacobian_file=None,
distance_type='radial')
# Unpack the results and calculate the adjustment
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh)
# Pickle results for later
log.info("Pickling results")
output = open('mesh.pickle', 'w')
pickle.dump(mesh, output)
output.close()
fig.scene.background = (1, 1, 1)
fig.scene.camera.yaw(230)
plot = vis.plot_prism_mesh(mesh, opacity=0.4)
plot = vis.plot_prism_mesh(seed_mesh)
axes = mlab.axes(plot,
nb_labels=5,
extent=[xmin, xmax, ymin, ymax, -zmax, -zmin])
mlab.show()
# Run the inversion
results = gplant.grow(data,
mesh,
seeds,
compactness=10**(5),
power=5,
norm=1,
threshold=5 * 10**(-5),
jacobian_file=None,
distance_type='radial')
estimate, residuals, misfits, goals = results
adjusted = gplant.adjustment(data, residuals)
fatiando.mesh.fill(estimate, mesh, fillNone=False)
log.info("Pickling results")
output = open('mesh.pickle', 'w')
pickle.dump(mesh, output)