GravMag: 3D imaging using the Generalized Inverse method on synthetic gravity data (more complex model + noisy data)¶

"""
GravMag: 3D imaging using the Generalized Inverse method on synthetic gravity
data (more complex model + noisy data)
"""
from fatiando import gridder, mesher, utils
from fatiando.gravmag import prism, imaging
from fatiando.vis import mpl, myv

# Make some synthetic gravity data from a simple prism model
model = [
    mesher.Prism(-4000, -1000, -4000, -2000, 2000, 5000, {'density': 800}),
    mesher.Prism(-1000, 1000, -1000, 1000, 1000, 6000, {'density': -800}),
    mesher.Prism(2000, 4000, 3000, 4000, 0, 4000, {'density': 600})]
shape = (25, 25)
xp, yp, zp = gridder.regular((-5000, 5000, -5000, 5000), shape, z=-10)
gz = utils.contaminate(prism.gz(xp, yp, zp, model), 0.1)

# Plot the data
mpl.figure()
mpl.axis('scaled')
mpl.contourf(yp, xp, gz, shape, 30)
mpl.colorbar()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
mpl.m2km()
mpl.show()

# Run the Generalized Inverse
mesh = imaging.geninv(xp, yp, zp, gz, shape,
                      0, 10000, 25)

# Plot the results
myv.figure()
myv.prisms(model, 'density', style='wireframe')
myv.prisms(mesh, 'density', edges=False, linewidth=5)
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.show()