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()
"""
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()
mpl.axis('scaled')
mpl.title('No weights: Observed (color) vs Predicted (black)')
levels = mpl.contourf(y, x, gz, shape, 17)
mpl.colorbar()
mpl.contour(y, x, predicted[0], shape, levels, color='k')
mpl.m2km()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
myv.figure()
plot = myv.prisms(model, 'density', style='wireframe', linewidth=4)
plot.actor.mapper.scalar_visibility = False
myv.prisms(bodies, 'density')
myv.axes(myv.outline(bounds))
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.title('No weights')
# Run the inversion again with weights
weights = gravmag.harvester.weights(x, y, seeds, [2000], decay=6)
data = [gravmag.harvester.Gz(x, y, z, gz, weights=weights)]
estimate, predicted = gravmag.harvester.harvest(data,
seeds,
mesh,
compactness=1.5,
threshold=0.001)
mesh.addprop('density', estimate['density'])
bodies = mesher.vremove(0, 'density', mesh)
mpl.figure()
mpl.axis('scaled')
mpl.title('With weights: Observed (color) vs Predicted (black)')
levels = mpl.contourf(y, x, gz, shape, 17)
#--- end iterations
oTimeEndTot = datetime.now()
oTimeEndIteration = datetime.now()
print("~~~~~~~~~~Total Time:", oTimeEndTot - oTimeBeginTot)
oTimeBeforePlotting = datetime.now()
#-----Drawing-----
#Plot the model
myv.figure()
myv.prisms(lModel, 'density', style='surface')
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.title("Geological Model")
# Plot the forward modelled signal
mpl.figure(figsize=(16, 5))
mpl.subplot(121)
mpl.title("Original signal")
mpl.axis('scaled')
mpl.contourf(aYGridCoords, aXGridCoords, aObservedSignal, tSignalSize,
50) #last arg is number of contours
mpl.colorbar()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
mpl.m2km()
mpl.subplot(122)
mpl.title("Forward modelled signal")
mpl.figure()
titles = ['Gravity anomaly', 'x derivative', 'y derivative', 'z derivative']
for i, f in enumerate([gz, xderiv, yderiv, zderiv]):
mpl.subplot(2, 2, i + 1)
mpl.title(titles[i])
mpl.axis('scaled')
mpl.contourf(yp, xp, f, shape, 50)
mpl.colorbar()
mpl.m2km()
mpl.show()
# Run the euler deconvolution on moving windows to produce a set of solutions
euler = Classic(xp, yp, zp, gz, xderiv, yderiv, zderiv, 2)
solver = MovingWindow(euler, windows=(10, 10), size=(2000, 2000)).fit()
mpl.figure()
mpl.axis('scaled')
mpl.title('Moving window centers')
mpl.contourf(yp, xp, gz, shape, 50)
mpl.points(solver.window_centers)
mpl.show()
myv.figure()
myv.points(solver.estimate_, size=100.)
myv.prisms(model, opacity=0.5)
axes = myv.axes(myv.outline(bounds), ranges=[b * 0.001 for b in bounds])
myv.wall_bottom(bounds)
myv.wall_north(bounds)
myv.title('Euler solutions')
myv.show()
"""
from fatiando.mesher import Prism, PolygonalPrism, Tesseroid
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)
mpl.axis('scaled')
mpl.title('No weights: Observed (color) vs Predicted (black)')
levels = mpl.contourf(y, x, gz, shape, 17)
mpl.colorbar()
mpl.contour(y, x, predicted[0], shape, levels, color='k')
mpl.m2km()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
myv.figure()
plot = myv.prisms(model, 'density', style='wireframe', linewidth=4)
plot.actor.mapper.scalar_visibility = False
myv.prisms(bodies, 'density')
myv.axes(myv.outline(bounds))
myv.wall_north(bounds)
myv.wall_bottom(bounds)
myv.title('No weights')
# Run the inversion again with weights
weights = gravmag.harvester.weights(x, y, seeds, [2000], decay=6)
data = [gravmag.harvester.Gz(x, y, z, gz, weights=weights)]
estimate, predicted = gravmag.harvester.harvest(data, seeds, mesh,
compactness=1.5, threshold=0.001)
mesh.addprop('density', estimate['density'])
bodies = mesher.vremove(0, 'density', mesh)
mpl.figure()
mpl.axis('scaled')
mpl.title('With weights: Observed (color) vs Predicted (black)')
levels = mpl.contourf(y, x, gz, shape, 17)
mpl.colorbar()
mpl.contour(y, x, predicted[0], shape, levels, color='k')
mpl.m2km()
oTimeEndTot = datetime.now()
oTimeEndIteration = datetime.now()
print("~~~~~~~~~~Total Time:", oTimeEndTot-oTimeBeginTot)
oTimeBeforePlotting = datetime.now()
#-----Drawing-----
#Plot the model
myv.figure()
myv.prisms(lModel, 'density', style='surface')
axes = myv.axes(myv.outline())
myv.wall_bottom(axes.axes.bounds)
myv.wall_north(axes.axes.bounds)
myv.title("Geological Model")
# Plot the forward modelled signal
mpl.figure(figsize=(16,5))
mpl.subplot(121)
mpl.title("Original signal")
mpl.axis('scaled')
mpl.contourf(aYGridCoords, aXGridCoords, aObservedSignal, tSignalSize, 50) #last arg is number of contours
mpl.colorbar()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
mpl.m2km()
mpl.subplot(122)
mpl.title("Forward modelled signal")
mpl.figure()
titles = ['Gravity anomaly', 'x derivative', 'y derivative', 'z derivative']
for i, f in enumerate([gz, xderiv, yderiv, zderiv]):
mpl.subplot(2, 2, i + 1)
mpl.title(titles[i])
mpl.axis('scaled')
mpl.contourf(yp, xp, f, shape, 50)
mpl.colorbar()
mpl.m2km()
mpl.show()
# Run the euler deconvolution on moving windows to produce a set of solutions
euler = Classic(xp, yp, zp, gz, xderiv, yderiv, zderiv, 2)
solver = MovingWindow(euler, windows=(10, 10), size=(2000, 2000)).fit()
mpl.figure()
mpl.axis('scaled')
mpl.title('Moving window centers')
mpl.contourf(yp, xp, gz, shape, 50)
mpl.points(solver.window_centers)
mpl.show()
myv.figure()
myv.points(solver.estimate_, size=100.)
myv.prisms(model, opacity=0.5)
axes = myv.axes(myv.outline(bounds), ranges=[b * 0.001 for b in bounds])
myv.wall_bottom(bounds)
myv.wall_north(bounds)
myv.title('Euler solutions')
myv.show()
Sometimes things are too small on one dimension to plot properly. On the Earth,
this is usually the vertical dimension. The functions in
:mod:`fatiando.vis.myv` have a ``scale`` attribute to control how much
exaggeration should be placed in each dimension of your plot.
"""
import copy
from fatiando.vis import myv
from fatiando.mesher import Prism
# Make two objects that are very thin.
model = [Prism(0, 1000, 0, 1000, 0, 10, props={'density': 300}),
Prism(-2500, -1000, -2000, -500, 0, 5, props={'density': -300})]
bounds = [-3000, 3000, -3000, 3000, 0, 20]
# The scale argument is by how much each dimension (being x, y, and z) will be
# multiplied. This means 300x in the z dimension.
scale = (1, 1, 300)
# Pass "scale" along to all plot functions
myv.figure()
myv.prisms(model, prop='density', scale=scale)
myv.axes(myv.outline(bounds, scale=scale), ranges=bounds)
myv.wall_north(bounds, scale=scale)
myv.wall_bottom(bounds, scale=scale)
# Note: the tittle can't be the first thing on the plot.
myv.title('{}x vertical exaggeration'.format(scale[-1]))
myv.show()
"""
from fatiando.mesher import Prism, PolygonalPrism, Tesseroid
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)
