area = [0, 540000, 0, 90000]
# Make a density and wave velocity model
density = 2400 * np.ones(shape)
svel = 3700 * np.ones(shape)
pvel = 6600 * np.ones(shape)
moho = 50
density[moho:] = 2800
svel[moho:] = 4300
pvel[moho:] = 7500
mu = wavefd.lame_mu(svel, density)
lamb = wavefd.lame_lamb(pvel, svel, density)
# Make a wave source from a mexican hat wavelet for the x and z directions
sources = [[
wavefd.MexHatSource(10000, 10000, area, shape, 100000, 0.5, delay=2)
], [wavefd.MexHatSource(10000, 10000, area, shape, 100000, 0.5, delay=2)]]
# Get the iterator. This part only generates an iterator object. The actual
# computations take place at each iteration in the for loop below
dt = wavefd.maxdt(area, shape, pvel.max())
duration = 130
maxit = int(duration / dt)
stations = [[400000, 0]]
snapshots = int(1. / dt)
simulation = wavefd.elastic_psv(lamb,
mu,
density,
area,
dt,
maxit,
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of the finite difference grid
shape = (200, 200)
area = [0, 60000, 0, 60000]
# Make a density and S wave velocity model
density = 2400 * np.ones(shape)
pvel = 6600
svel = 3700
mu = wavefd.lame_mu(svel, density)
lamb = wavefd.lame_lamb(pvel, svel, density)
# Make a wave source from a mexican hat wavelet that vibrates in the x and z
# directions equaly
sources = [[wavefd.MexHatSource(30000, 40000, area, shape, 10000, 1, delay=1)],
[wavefd.MexHatSource(30000, 40000, area, shape, 10000, 1, delay=1)]]
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, pvel)
duration = 20
maxit = int(duration / dt)
stations = [[55000, 0]] # x, z coordinate of the seismometer
snapshot = int(0.5 / dt) # Plot a snapshot of the simulation every 0.5 seconds
simulation = wavefd.elastic_psv(lamb,
mu,
density,
area,
dt,
maxit,
sources,
import numpy as np
from matplotlib import animation
from fatiando import gridder
from fatiando.seismic import wavefd
from fatiando.vis import mpl
# Set the parameters of the finite difference grid
shape = (150, 150)
area = [0, 60000, 0, 60000]
# Make a density and S wave velocity model
density = 2400 * np.ones(shape)
velocity = 3700
mu = wavefd.lame_mu(velocity, density)
# Make a wave source from a mexican hat wavelet
sources = [wavefd.MexHatSource(30000, 15000, area, shape, 100, 1, delay=2)]
# Get the iterator for the simulation
dt = wavefd.maxdt(area, shape, velocity)
duration = 20
maxit = int(duration / dt)
stations = [[50000, 0]] # x, z coordinate of the seismometer
snapshot = int(0.5 / dt) # Plot a snapshot of the simulation every 0.5 seconds
simulation = wavefd.elastic_sh(mu,
density,
area,
dt,
maxit,
sources,
stations,
snapshot,