def run(title):
if title == 'Migration':
result = gravmag.imaging.migrate(xp, yp, zp, gz, bounds[-2], bounds[-1],
meshshape, power=0.5)
elif title == 'Generalized Inverse':
result = gravmag.imaging.geninv(xp, yp, zp, gz, meshshape[1:],
bounds[-2], bounds[-1], meshshape[0])
elif title == 'Sandwich':
result = gravmag.imaging.sandwich(xp, yp, zp, gz, meshshape[1:],
bounds[-2], bounds[-1], meshshape[0], power=0.5)
# Plot the results
myv.figure()
myv.polyprisms(prisms, 'density', style='wireframe', linewidth=2)
myv.prisms(result, 'density', edges=False)
axes = myv.axes(myv.outline(), ranges=[b*0.001 for b in bounds],
fmt='%.0f')
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.title(title)
myv.show()
area = bounds[:4]
axis = mpl.figure().gca()
mpl.axis('scaled')
model = [
mesher.PolygonalPrism(
mpl.draw_polygon(area, axis, xy2ne=True),
# Use only induced magnetization
0, 2000, {'magnetization':2})]
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-500)
tf = polyprism.tf(xp, yp, zp, model, inc, dec)
# and plot it
mpl.figure()
mpl.axis('scaled')
mpl.title("Total field anomalyproduced by prism model (nT)")
mpl.contourf(yp, xp, tf, shape, 20)
mpl.colorbar()
for p in model:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.m2km()
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(model, 'magnetization')
myv.axes(myv.outline(bounds), ranges=[i*0.001 for i in bounds])
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.show()
fields = [prism.potential(xp, yp, zp, model),
prism.gx(xp, yp, zp, model),
prism.gy(xp, yp, zp, model),
prism.gz(xp, yp, zp, model),
prism.gxx(xp, yp, zp, model),
prism.gxy(xp, yp, zp, model),
prism.gxz(xp, yp, zp, model),
prism.gyy(xp, yp, zp, model),
prism.gyz(xp, yp, zp, model),
prism.gzz(xp, yp, zp, model)]
titles = ['potential', 'gx', 'gy', 'gz',
'gxx', 'gxy', 'gxz', 'gyy', 'gyz', 'gzz']
mpl.figure(figsize=(8, 9))
mpl.subplots_adjust(left=0.03, right=0.95, bottom=0.05, top=0.92, hspace=0.3)
mpl.suptitle("Potential fields produced by a 3 prism model")
for i, field in enumerate(fields):
mpl.subplot(4, 3, i + 3)
mpl.axis('scaled')
mpl.title(titles[i])
levels = mpl.contourf(yp*0.001, xp*0.001, field, shape, 15)
cb = mpl.colorbar()
mpl.contour(yp*0.001, xp*0.001, field, shape, levels, clabel=False, linewidth=0.1)
mpl.show()
myv.figure()
myv.prisms(model, prop='density')
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds, opacity=0.2)
myv.wall_north(axes.axes.bounds)
myv.show()
utils.contaminate(gravmag.prism.gxy(xp, yp, zp, prisms), noise),
utils.contaminate(gravmag.prism.gxz(xp, yp, zp, prisms), noise),
utils.contaminate(gravmag.prism.gyy(xp, yp, zp, prisms), noise),
utils.contaminate(gravmag.prism.gyz(xp, yp, zp, prisms), noise),
utils.contaminate(gravmag.prism.gzz(xp, yp, zp, prisms), noise)
]
# Plot the data
titles = ['gxx', 'gxy', 'gxz', 'gyy', 'gyz', 'gzz']
mpl.figure()
for i, title in enumerate(titles):
mpl.subplot(3, 2, i + 1)
mpl.title(title)
mpl.axis('scaled')
levels = mpl.contourf(yp, xp, tensor[i], shape, 10)
mpl.contour(yp, xp, tensor[i], shape, levels)
mpl.m2km()
mpl.show()
# Get the eigenvectors from the tensor data
eigenvals, eigenvecs = gravmag.tensor.eigen(tensor)
# Use the first eigenvector to estimate the center of mass
cm, sigma = gravmag.tensor.center_of_mass(xp, yp, zp, eigenvecs[0])
print "Sigma = %g" % (sigma)
# Plot the prism and the estimated center of mass
myv.figure()
myv.points([cm], size=300.)
myv.prisms(prisms, prop='density', opacity=0.5)
axes = myv.axes(myv.outline(extent=[-5000, 5000, -5000, 5000, 0, 5000]))
myv.wall_bottom(axes.axes.bounds, opacity=0.2)
myv.wall_north(axes.axes.bounds)
myv.show()
mesher.Prism(-1000, 1000, -1000, 1000, 1000, 7000, {'density': -800}),
mesher.Prism(2000, 4000, 3000, 4000, 0, 2000, {'density': 600})
]
# Calculate on a scatter of points to show that migration doesn't need gridded
# data
xp, yp, zp = gridder.scatter((-6000, 6000, -6000, 6000), 1000, z=-10)
gz = utils.contaminate(prism.gz(xp, yp, zp, model), 0.1)
# Plot the data
shape = (50, 50)
mpl.figure()
mpl.axis('scaled')
mpl.contourf(yp, xp, gz, shape, 30, interp=True)
mpl.colorbar()
mpl.plot(yp, xp, '.k')
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
mpl.m2km()
mpl.show()
mesh = imaging.migrate(xp, yp, zp, gz, 0, 10000, (30, 30, 30), power=0.8)
# Plot the results
myv.figure()
myv.prisms(model, 'density', style='wireframe', linewidth=2)
myv.prisms(mesh, 'density', edges=False)
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.show()
area = bounds[:4]
axis = mpl.figure().gca()
mpl.axis('scaled')
model = [
mesher.PolygonalPrism(
mpl.draw_polygon(area, axis, xy2ne=True),
# Use only induced magnetization
0, 2000, {'magnetization': 2})]
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-500)
tf = polyprism.tf(xp, yp, zp, model, inc, dec)
# and plot it
mpl.figure()
mpl.axis('scaled')
mpl.title("Total field anomalyproduced by prism model (nT)")
mpl.contourf(yp, xp, tf, shape, 20)
mpl.colorbar()
for p in model:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.m2km()
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(model, 'magnetization')
myv.axes(myv.outline(bounds), ranges=[i * 0.001 for i in bounds])
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.show()
"""
Vis: Exaggerate the vertical dimension of 3D plots
"""
from fatiando.mesher import Prism, PolygonalPrism
from fatiando.vis import myv
prism = Prism(0, 1000, 0, 1000, 0, 10)
poly = PolygonalPrism([[-2000, -2000], [-1000, -1000], [-2000, -1000]], 0, 10)
bounds = (-3000, 3000, -3000, 3000, 0, 20)
myv.figure()
myv.prisms([prism])
myv.polyprisms([poly])
myv.axes(myv.outline(bounds))
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.title('No exaggeration')
scale = (1, 1, 50) # Exaggerate 50x the z axis
myv.figure()
myv.prisms([prism], scale=scale)
myv.polyprisms([poly], scale=scale)
myv.axes(myv.outline(bounds, scale=scale), ranges=bounds)
myv.wall_north(bounds, scale=scale)
myv.wall_bottom(bounds, scale=scale)
myv.title('50x exaggeration')
myv.show()
from fatiando import gridder, mesher
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(-1000,1000,-2000,2000,2000,4000,{'density':500})]
shape = (25, 25)
xp, yp, zp = gridder.regular((-5000, 5000, -5000, 5000), shape, z=-10)
gz = prism.gz(xp, yp, zp, model)
# 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()
mesh = imaging.sandwich(xp, yp, zp, gz, shape, 0, 10000, 25)
# Plot the results
myv.figure()
myv.prisms(model, 'density', style='wireframe', linewidth=2)
myv.prisms(mesh, 'density', edges=False)
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.show()
