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()
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()
locations = [[x, y, 1500, {'density': 1000}] for x, y in zip(seedx, seedy)]
mpl.show()
# Make the seed and set the compactness regularizing parameter mu
seeds = harvester.sow(locations, mesh)
# Run the inversion
estimate, predicted = harvester.harvest(data, seeds, mesh,
compactness=0.05, threshold=0.0005)
# Put the estimated density values in the mesh
mesh.addprop('density', estimate['density'])
# Plot the adjustment and the result
mpl.figure()
mpl.title("True: color | Predicted: contour")
mpl.axis('scaled')
levels = mpl.contourf(yp, xp, gz, shape, 12)
mpl.colorbar()
mpl.contour(yp, xp, predicted[0], shape, levels, color='k')
mpl.xlabel('Horizontal coordinate y (km)')
mpl.ylabel('Horizontal coordinate x (km)')
mpl.m2km()
mpl.show()
# Plot the result
myv.figure()
myv.polyprisms(model, 'density', opacity=0.6, linewidth=5)
myv.prisms(vremove(0, 'density', mesh), 'density')
myv.prisms(seeds, 'density')
myv.axes(myv.outline(bounds), ranges=[i * 0.001 for i in bounds], fmt='%.1f',
nlabels=6)
myv.wall_bottom(bounds)
myv.wall_north(bounds)
myv.show()
area = bounds[:4]
axis = mpl.figure().gca()
mpl.axis('scaled')
prisms = [
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 = gravmag.polyprism.tf(xp, yp, zp, prisms, 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 prisms:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.m2km()
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(prisms, 'magnetization')
myv.axes(myv.outline(bounds), ranges=[i*0.001 for i in bounds])
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.show()
data = [
polyprism.gxx(xp, yp, zp, model),
polyprism.gxy(xp, yp, zp, model),
polyprism.gxz(xp, yp, zp, model),
polyprism.gyy(xp, yp, zp, model),
polyprism.gyz(xp, yp, zp, model),
polyprism.gzz(xp, yp, zp, model)
]
# and plot it
titles = ['gxx', 'gxy', 'gxz', 'gyy', 'gyz', 'gzz']
mpl.figure()
mpl.axis('scaled')
mpl.suptitle("Gravity tensor produced by prism model (Eotvos)")
for i in xrange(len(data)):
mpl.subplot(3, 2, i + 1)
mpl.title(titles[i])
mpl.contourf(yp, xp, data[i], 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, 'density')
myv.axes(myv.outline(bounds), ranges=[i * 0.001 for i in bounds])
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.show()
estimate, predicted = gm.harvester.harvest(data,
seeds,
mesh,
compactness=0.05,
threshold=0.0005)
# Put the estimated density values in the mesh
mesh.addprop('density', estimate['density'])
# Plot the adjustment and the result
mpl.figure()
mpl.title("True: color | Predicted: contour")
mpl.axis('scaled')
levels = mpl.contourf(yp, xp, gz, shape, 12)
mpl.colorbar()
mpl.contour(yp, xp, predicted[0], shape, levels, color='k')
mpl.xlabel('Horizontal coordinate y (km)')
mpl.ylabel('Horizontal coordinate x (km)')
mpl.m2km()
mpl.show()
# Plot the result
myv.figure()
myv.polyprisms(model, 'density', opacity=0.6, linewidth=5)
myv.prisms(vremove(0, 'density', mesh), 'density')
myv.prisms(seeds, 'density')
myv.axes(myv.outline(bounds),
ranges=[i * 0.001 for i in bounds],
fmt='%.1f',
nlabels=6)
myv.wall_bottom(bounds)
myv.wall_north(bounds)
myv.show()
depths = [0, 1000, 2000, 3000, 4000]
prisms = []
for i in range(1, len(depths)):
axes = mpl.figure().gca()
mpl.axis('scaled')
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
prisms.append(
mesher.PolygonalPrism(
mpl.draw_polygon(area, axes, xy2ne=True),
depths[i - 1], depths[i], {'density':500}))
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-1)
gz = gravmag.polyprism.gz(xp, yp, zp, prisms)
# and plot it
mpl.figure()
mpl.axis('scaled')
mpl.title("gz produced by prism model (mGal)")
mpl.contourf(yp, xp, gz, shape, 20)
mpl.colorbar()
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(prisms, 'density')
myv.axes(myv.outline(bounds), ranges=[i*0.001 for i in bounds])
myv.show()
depths = [0, 1000, 2000, 3000, 4000]
model = []
for i in range(1, len(depths)):
axes = mpl.figure().gca()
mpl.axis('scaled')
for p in model:
mpl.polygon(p, '.-k', xy2ne=True)
model.append(
mesher.PolygonalPrism(
mpl.draw_polygon(area, axes, xy2ne=True),
depths[i - 1], depths[i], {'density':500}))
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-1)
gz = polyprism.gz(xp, yp, zp, model)
# and plot it
mpl.figure()
mpl.axis('scaled')
mpl.title("gz produced by prism model (mGal)")
mpl.contourf(yp, xp, gz, shape, 20)
mpl.colorbar()
for p in model:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.show()
# Show the model
myv.figure()
myv.polyprisms(model, 'density')
myv.axes(myv.outline(bounds), ranges=[i*0.001 for i in bounds])
myv.show()
tesseroid = Tesseroid(10, 20, 50, 60, 10**6, 0)
red, green, blue = (1, 0, 0), (0, 1, 0), (0, 0, 1)
white, black = (1, 1, 1), (0, 0, 0),
myv.figure()
# Make the prism red with blue edges, despite its density
myv.prisms([prism], 'density', color=red, edgecolor=blue)
# and the polyprism green with blue edges
myv.title('Body + edge colors')
myv.figure()
# For wireframes, color is usually set by the density.
# Overwrite this by setting *color*
# *edgecolor* is ignored
myv.polyprisms([polyprism],
'density',
style='wireframe',
color=green,
edgecolor=red,
linewidth=2)
myv.title('Wireframe colors')
# Black background, white lines, green tesseroid
myv.figure(zdown=False, color=black)
myv.earth()
myv.continents(color=white)
myv.tesseroids([tesseroid], color=green, edgecolor=white)
myv.title('Black background', color=white)
myv.show()
area = bounds[:4]
depths = [0, 1000, 2000, 3000, 4000]
prisms = []
for i in range(1, len(depths)):
axes = mpl.figure().gca()
mpl.axis('scaled')
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
prisms.append(
mesher.PolygonalPrism(mpl.draw_polygon(area, axes, xy2ne=True),
depths[i - 1], depths[i], {'density': 500}))
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-1)
gz = gravmag.polyprism.gz(xp, yp, zp, prisms)
# and plot it
mpl.figure()
mpl.axis('scaled')
mpl.title("gz produced by prism model (mGal)")
mpl.contourf(yp, xp, gz, shape, 20)
mpl.colorbar()
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(prisms, 'density')
myv.axes(myv.outline(bounds), ranges=[i * 0.001 for i in bounds])
myv.show()
from fatiando.vis import myv
prism = Prism(1, 2, 1, 2, 0, 1, {'density': 1})
polyprism = PolygonalPrism([[3, 1], [4, 2], [5, 1]], -1, 2, {'density': 2})
tesseroid = Tesseroid(10, 20, 50, 60, 10 ** 6, 0)
red, green, blue = (1, 0, 0), (0, 1, 0), (0, 0, 1)
white, black = (1, 1, 1), (0, 0, 0),
myv.figure()
# Make the prism red with blue edges, despite its density
myv.prisms([prism], 'density', color=red, edgecolor=blue)
# and the polyprism green with blue edges
myv.title('Body + edge colors')
myv.figure()
# For wireframes, color is usually set by the density.
# Overwrite this by setting *color*
# *edgecolor* is ignored
myv.polyprisms([polyprism], 'density', style='wireframe', color=green,
edgecolor=red, linewidth=2)
myv.title('Wireframe colors')
# Black background, white lines, green tesseroid
myv.figure(zdown=False, color=black)
myv.earth()
myv.continents(color=white)
myv.tesseroids([tesseroid], color=green, edgecolor=white)
myv.title('Black background', color=white)
myv.show()
prisms = [
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 = gravmag.polyprism.tf(xp, yp, zp, prisms, 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 prisms:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
mpl.m2km()
mpl.show()
# Show the prisms
myv.figure()
myv.polyprisms(prisms, 'magnetization')
myv.axes(myv.outline(bounds), ranges=[i * 0.001 for i in bounds])
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.show()