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)
mpl.m2km()
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
# and plot it
"""
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')
GravMag: Forward gravity modeling using a stack of 3D polygonal prisms
"""
from fatiando import mesher, gridder, gravmag
from fatiando.vis import mpl, myv
bounds = [-10000, 10000, -10000, 10000, 0, 5000]
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