def setUp(self):
cs = 25.0
hx = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hy = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hz = [(cs, 0, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy, hz], x0="CCN")
blkind0 = utils.model_builder.getIndicesSphere(
np.r_[-100.0, -100.0, -200.0], 75.0, mesh.gridCC)
blkind1 = utils.model_builder.getIndicesSphere(
np.r_[100.0, 100.0, -200.0], 75.0, mesh.gridCC)
sigma = np.ones(mesh.nC) * 1e-2
eta = np.zeros(mesh.nC)
tau = np.ones_like(sigma) * 1.0
eta[blkind0] = 0.1
eta[blkind1] = 0.1
tau[blkind0] = 0.1
tau[blkind1] = 0.01
x = mesh.vectorCCx[(mesh.vectorCCx > -155.0)
& (mesh.vectorCCx < 155.0)]
y = mesh.vectorCCy[(mesh.vectorCCy > -155.0)
& (mesh.vectorCCy < 155.0)]
Aloc = np.r_[-200.0, 0.0, 0.0]
Bloc = np.r_[200.0, 0.0, 0.0]
M = utils.ndgrid(x - 25.0, y, np.r_[0.0])
N = utils.ndgrid(x + 25.0, y, np.r_[0.0])
times = np.arange(10) * 1e-3 + 1e-3
rx = sip.receivers.Dipole(M, N, times)
print(rx.nD)
print(rx.locations)
src = sip.sources.Dipole([rx], Aloc, Bloc)
survey = sip.Survey([src])
print(f"Survey ND = {survey.nD}")
print(f"Survey ND = {src.nD}")
wires = maps.Wires(("eta", mesh.nC), ("taui", mesh.nC))
problem = sip.Simulation3DCellCentered(
mesh,
survey=survey,
rho=1.0 / sigma,
etaMap=wires.eta,
tauiMap=wires.taui,
storeJ=False,
)
problem.solver = Solver
mSynth = np.r_[eta, 1.0 / tau]
problem.model = mSynth
dobs = problem.make_synthetic_data(mSynth, add_noise=True)
# Now set up the problem to do some minimization
dmis = data_misfit.L2DataMisfit(data=dobs, simulation=problem)
reg = regularization.Tikhonov(mesh)
opt = optimization.InexactGaussNewton(maxIterLS=20,
maxIter=10,
tolF=1e-6,
tolX=1e-6,
tolG=1e-6,
maxIterCG=6)
invProb = inverse_problem.BaseInvProblem(dmis, reg, opt, beta=1e4)
inv = inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
self.dobs = dobs
def setUp(self):
cs = 25.0
hx = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hy = [(cs, 0, -1.3), (cs, 21), (cs, 0, 1.3)]
hz = [(cs, 0, -1.3), (cs, 20), (cs, 0, 1.3)]
mesh = discretize.TensorMesh([hx, hy, hz], x0="CCC")
blkind0 = utils.model_builder.getIndicesSphere(
np.r_[-100.0, -100.0, -200.0], 75.0, mesh.gridCC)
blkind1 = utils.model_builder.getIndicesSphere(
np.r_[100.0, 100.0, -200.0], 75.0, mesh.gridCC)
sigma = np.ones(mesh.nC) * 1e-2
airind = mesh.gridCC[:, 2] > 0.0
sigma[airind] = 1e-8
eta = np.zeros(mesh.nC)
tau = np.ones_like(sigma) * 1.0
c = np.ones_like(sigma) * 0.5
eta[blkind0] = 0.1
eta[blkind1] = 0.1
tau[blkind0] = 0.1
tau[blkind1] = 0.01
actmapeta = maps.InjectActiveCells(mesh, ~airind, 0.0)
actmaptau = maps.InjectActiveCells(mesh, ~airind, 1.0)
actmapc = maps.InjectActiveCells(mesh, ~airind, 1.0)
x = mesh.vectorCCx[(mesh.vectorCCx > -155.0)
& (mesh.vectorCCx < 155.0)]
y = mesh.vectorCCy[(mesh.vectorCCy > -155.0)
& (mesh.vectorCCy < 155.0)]
Aloc = np.r_[-200.0, 0.0, 0.0]
Bloc = np.r_[200.0, 0.0, 0.0]
M = utils.ndgrid(x - 25.0, y, np.r_[0.0])
N = utils.ndgrid(x + 25.0, y, np.r_[0.0])
times = np.arange(10) * 1e-3 + 1e-3
rx = sip.receivers.Dipole(M, N, times)
src = sip.sources.Dipole([rx], Aloc, Bloc)
survey = sip.Survey([src])
wires = maps.Wires(("eta", actmapeta.nP), ("taui", actmaptau.nP),
("c", actmapc.nP))
problem = sip.Simulation3DNodal(
mesh,
survey=survey,
sigma=sigma,
etaMap=actmapeta * wires.eta,
tauiMap=actmaptau * wires.taui,
cMap=actmapc * wires.c,
actinds=~airind,
storeJ=False,
verbose=False,
)
problem.solver = Solver
mSynth = np.r_[eta[~airind], 1.0 / tau[~airind], c[~airind]]
dobs = problem.make_synthetic_data(mSynth, add_noise=True)
# Now set up the problem to do some minimization
dmis = data_misfit.L2DataMisfit(data=dobs, simulation=problem)
reg_eta = regularization.Sparse(mesh,
mapping=wires.eta,
indActive=~airind)
reg_taui = regularization.Sparse(mesh,
mapping=wires.taui,
indActive=~airind)
reg_c = regularization.Sparse(mesh, mapping=wires.c, indActive=~airind)
reg = reg_eta + reg_taui + reg_c
opt = optimization.InexactGaussNewton(maxIterLS=20,
maxIter=10,
tolF=1e-6,
tolX=1e-6,
tolG=1e-6,
maxIterCG=6)
invProb = inverse_problem.BaseInvProblem(dmis, reg, opt, beta=1e4)
inv = inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
self.dobs = dobs