def test_full_model():
shape = (50, 50, 50)
spacing = [10. for _ in shape]
nbpml = 10
# Create two-layer model from preset
model = demo_model(preset='layers-isotropic',
vp_top=1.,
vp_bottom=2.,
spacing=spacing,
shape=shape,
nbpml=nbpml)
# Test Model pickling
pkl_model = pickle.dumps(model)
new_model = pickle.loads(pkl_model)
assert np.isclose(np.linalg.norm(model.vp - new_model.vp), 0)
f0 = .010
dt = model.critical_dt
t0 = 0.0
tn = 350.0
time_range = TimeAxis(start=t0, stop=tn, step=dt)
# Test TimeAxis pickling
pkl_time_range = pickle.dumps(time_range)
new_time_range = pickle.loads(pkl_time_range)
assert np.isclose(np.linalg.norm(time_range.time_values),
np.linalg.norm(new_time_range.time_values))
# Test Class Constant pickling
pkl_origin = pickle.dumps(model.grid.origin)
new_origin = pickle.loads(pkl_origin)
for a, b in zip(model.grid.origin, new_origin):
assert a.compare(b) == 0
# Test Class TimeDimension pickling
time_dim = TimeDimension(name='time',
spacing=Constant(name='dt', dtype=np.float32))
pkl_time_dim = pickle.dumps(time_dim)
new_time_dim = pickle.loads(pkl_time_dim)
assert time_dim.spacing._value == new_time_dim.spacing._value
# Test Class SteppingDimension
stepping_dim = SteppingDimension(name='t', parent=time_dim)
pkl_stepping_dim = pickle.dumps(stepping_dim)
new_stepping_dim = pickle.loads(pkl_stepping_dim)
assert stepping_dim.is_Time == new_stepping_dim.is_Time
# Test Grid pickling
pkl_grid = pickle.dumps(model.grid)
new_grid = pickle.loads(pkl_grid)
assert model.grid.shape == new_grid.shape
assert model.grid.extent == new_grid.extent
assert model.grid.shape == new_grid.shape
for a, b in zip(model.grid.dimensions, new_grid.dimensions):
assert a.compare(b) == 0
ricker = RickerSource(name='src',
grid=model.grid,
f0=f0,
time_range=time_range)
pkl_ricker = pickle.dumps(ricker)
new_ricker = pickle.loads(pkl_ricker)
assert np.isclose(np.linalg.norm(ricker.data),
np.linalg.norm(new_ricker.data))
from devito import Grid, Function, TimeFunction, NODE, Eq, Operator
from examples.seismic.source import RickerSource, TimeAxis
from numpy import sqrt
import matplotlib.pyplot as plt
extent = (150., 150.)
shape = (301, 301)
grid = Grid(extent=extent, shape=shape)
t0, tn = 0., 40. # Strange tiling effect at tn > 30
dt = (1. / sqrt(2.)) / 2500.
time_range = TimeAxis(start=t0, stop=tn,
step=dt) #Set up time axis object for ricker source
src = RickerSource(name='src', grid=grid, f0=0.100,
time_range=time_range) # Ricker wavelet source
src.coordinates.data[:] = [75., 75.]
so = 6 # Spatial derivatives are second order accurate
x = grid.dimensions[0]
y = grid.dimensions[1]
#vx= TimeFunction(name='vx', grid=grid, staggered=x, space_order=so)
#vy = TimeFunction(name='vy', grid=grid, staggered=y, space_order=so)
#txx = TimeFunction(name='txx', grid=grid, staggered=NODE, space_order=so)
#tyy = TimeFunction(name='tyy', grid=grid, staggered=NODE, space_order=so)
#txy = TimeFunction(name='txy', grid=grid, staggered=(x, y), space_order=so)
#Fairly sure grid is actually 2km x 2km with spacing 10m
shape = (201, 201)
#Define x and z as spatial dimentions for Sympy
x = SpaceDimension(name='x',
spacing=Constant(name='h_x',
value=extent[0] / (shape[0] - 1)))
#Dimension called x, with constant spacing of 10 (called h_x)
z = SpaceDimension(name='z',
spacing=Constant(name='h_z',
value=extent[1] / (shape[1] - 1)))
grid = Grid(extent=extent, shape=shape, dimensions=(x, z))
# Timestep size from Eq. 7 with V_p=6000. and dx=100
t0, tn = 0., 600.
dt = (10. / np.sqrt(2.)) / 6.
time_range = TimeAxis(start=t0, stop=tn, step=dt)
src = RickerSource(name='src', grid=grid, f0=0.01, time_range=time_range)
src.coordinates.data[:] = np.array([1000., 1000.])
src.show()
# Now that looks pretty! But let's do it again with a higher order...
so = 6
vx = TimeFunction(name='vx', grid=grid, staggered=x, space_order=so)
vz = TimeFunction(name='vz', grid=grid, staggered=z, space_order=so)
txx = TimeFunction(name='txx', grid=grid, staggered=NODE, space_order=so)
tzz = TimeFunction(name='tzz', grid=grid, staggered=NODE, space_order=so)
txz = TimeFunction(name='txz', grid=grid, staggered=(x, z), space_order=so)
print("vx.dx stencil", vx.dx, "\n\n")
print("vx.dz stencil", vx.dz, "\n\n")