prisms
"""
from fatiando import mesher, gridder, utils
from fatiando.vis import mpl, myv
from fatiando.gravmag import polyprism
# The regional field
inc, dec = 30, -15
# Draw each polygonal prism (viewed from above)
bounds = [-5000, 5000, -5000, 5000, 0, 5000]
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)
prisms
"""
from fatiando import mesher, gridder, utils
from fatiando.vis import mpl, myv
from fatiando.gravmag import polyprism
# The regional field
inc, dec = 30, -15
# Draw each polygonal prism (viewed from above)
bounds = [-5000, 5000, -5000, 5000, 0, 5000]
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)
"""
GravMag: 2D forward modeling with polygons
"""
import numpy
from fatiando import utils, mesher
from fatiando.gravmag import talwani
from fatiando.vis import mpl
# Notice that the last two number are switched.
# This way, the z axis in the plots points down.
area = (-5000, 5000, 5000, 0)
axes = mpl.figure().gca()
mpl.xlabel("X")
mpl.ylabel("Z")
mpl.axis('scaled')
polygons = [mesher.Polygon(mpl.draw_polygon(area, axes), {'density': 500})]
xp = numpy.arange(-4500, 4500, 100)
zp = numpy.zeros_like(xp)
gz = talwani.gz(xp, zp, polygons)
mpl.figure()
mpl.axis('scaled')
mpl.subplot(2, 1, 1)
mpl.title(r"Gravity anomaly produced by the model")
mpl.plot(xp, gz, '-k', linewidth=2)
mpl.ylabel("mGal")
mpl.xlim(-5000, 5000)
mpl.subplot(2, 1, 2)
mpl.polygon(polygons[0], 'o-k', linewidth=2, fill='k', alpha=0.5)
mpl.xlabel("X")
mpl.ylabel("Z")
"""
GravMag: 2D forward modeling with polygons
"""
import numpy
from fatiando import utils, mesher
from fatiando.gravmag import talwani
from fatiando.vis import mpl
# Notice that the last two number are switched.
# This way, the z axis in the plots points down.
area = (-5000, 5000, 5000, 0)
axes = mpl.figure().gca()
mpl.xlabel("X")
mpl.ylabel("Z")
mpl.axis('scaled')
polygons = [mesher.Polygon(mpl.draw_polygon(area, axes),
{'density': 500})]
xp = numpy.arange(-4500, 4500, 100)
zp = numpy.zeros_like(xp)
gz = talwani.gz(xp, zp, polygons)
mpl.figure()
mpl.axis('scaled')
mpl.subplot(2, 1, 1)
mpl.title(r"Gravity anomaly produced by the model")
mpl.plot(xp, gz, '-k', linewidth=2)
mpl.ylabel("mGal")
mpl.xlim(-5000, 5000)
mpl.subplot(2, 1, 2)
mpl.polygon(polygons[0], 'o-k', linewidth=2, fill='k', alpha=0.5)
mpl.xlabel("X")
"""
GravMag: 2D forward modeling with polygons
"""
import numpy
from fatiando import utils, mesher
from fatiando.gravmag import talwani
from fatiando.vis import mpl
# Notice that the last two number are switched.
# This way, the z axis in the plots points down.
area = (-5000, 5000, 5000, 0)
axes = mpl.figure().gca()
mpl.xlabel("X")
mpl.ylabel("Z")
mpl.axis('scaled')
polygons = [mesher.Polygon(mpl.draw_polygon(area, axes),
{'density':500})]
xp = numpy.arange(-4500, 4500, 100)
zp = numpy.zeros_like(xp)
gz = talwani.gz(xp, zp, polygons)
mpl.figure()
mpl.axis('scaled')
mpl.subplot(2,1,1)
mpl.title(r"Gravity anomaly produced by the model")
mpl.plot(xp, gz, '-k', linewidth=2)
mpl.ylabel("mGal")
mpl.xlim(-5000, 5000)
mpl.subplot(2,1,2)
mpl.polygon(polygons[0], 'o-k', linewidth=2, fill='k', alpha=0.5)
mpl.xlabel("X")
"""
GravMag: Generate synthetic gradient tensor data from polygonal prisms
"""
from fatiando import mesher, gridder
from fatiando.gravmag import polyprism
from fatiando.vis import mpl, myv
print "Draw the polygons one by one"
bounds = [-10000, 10000, -10000, 10000, 0, 5000]
area = bounds[:4]
axis = mpl.figure().gca()
mpl.axis('scaled')
model = [
mesher.PolygonalPrism(mpl.draw_polygon(area, axis, xy2ne=True), 0, 1000,
{'density': 500})
]
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(area, shape, z=-500)
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')
from fatiando.vis import mpl
print "Draw the polygons one by one"
area = [-10000, 10000, -10000, 10000]
dataarea = [-5000, 5000, -5000, 5000]
model = []
for depth in [5000, 5000]:
fig = mpl.figure()
mpl.axis('scaled')
mpl.square(dataarea)
for p in model:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
model.append(
mesher.PolygonalPrism(
mpl.draw_polygon(area, fig.gca(), xy2ne=True),
0, depth, {'density':500}))
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(dataarea, shape, z=-500)
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)]
# Calculate the 3 invariants
invariants = tensor.invariants(data)
data = data + invariants
# and plot it
log.info(logger.header())
log.info(__doc__)
log.info("Draw the polygons one by one")
area = [-10000, 10000, -10000, 10000]
dataarea = [-5000, 5000, -5000, 5000]
prisms = []
for depth in [5000, 5000]:
fig = mpl.figure()
mpl.axis('scaled')
mpl.square(dataarea)
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
mpl.set_area(area)
prisms.append(
mesher.PolygonalPrism(mpl.draw_polygon(area, fig.gca(), xy2ne=True), 0,
depth, {'density': 500}))
# Calculate the effect
shape = (100, 100)
xp, yp, zp = gridder.regular(dataarea, shape, z=-500)
tensor = [
gravmag.polyprism.gxx(xp, yp, zp, prisms),
gravmag.polyprism.gxy(xp, yp, zp, prisms),
gravmag.polyprism.gxz(xp, yp, zp, prisms),
gravmag.polyprism.gyy(xp, yp, zp, prisms),
gravmag.polyprism.gyz(xp, yp, zp, prisms),
gravmag.polyprism.gzz(xp, yp, zp, prisms)
]
# Calculate the 3 invariants
invariants = gravmag.tensor.invariants(tensor)
data = tensor + invariants
log.info(__doc__)
# Make some synthetic gravity data from a polygonal prism model
log.info("Draw the polygons one by one")
bounds = [-10000, 10000, -10000, 10000, 0, 10000]
area = bounds[:4]
depths = [0, 1000, 3000, 7000]
prisms = []
for i in range(1, len(depths)):
# Plot previous prisms
axes = mpl.figure().gca()
mpl.axis('scaled')
for p in prisms:
mpl.polygon(p, '.-k', xy2ne=True)
# Draw a new polygon
polygon = mpl.draw_polygon(area, axes, xy2ne=True)
# append the newly drawn one
prisms.append(
mesher.PolygonalPrism(polygon, depths[i - 1], depths[i],
{'density':500}))
meshshape = (30, 30, 30)
xp, yp, zp = gridder.regular(area, meshshape[1:], z=-10)
gz = gravmag.polyprism.gz(xp, yp, zp, prisms)
# Plot the data
mpl.figure()
mpl.axis('scaled')
mpl.contourf(yp, xp, gz, meshshape[1:], 30)
mpl.colorbar()
mpl.xlabel('East (km)')
mpl.ylabel('North (km)')
