def setUp(self):
cs = 12.5
hx = [(cs, 7, -1.3), (cs, 61), (cs, 7, 1.3)]
hy = [(cs, 7, -1.3), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = np.linspace(-135, 250.0, 20)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
N = utils.ndgrid(x + 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
# A1loc = np.r_[-130, 0.]
rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
data_ana = analytics.DCAnalytic_Pole_Dipole(np.r_[A0loc, 0.0],
rxloc,
sighalf,
earth_type="halfspace")
rx = dc.receivers.Dipole(M, N)
src0 = dc.sources.Pole([rx], A0loc)
survey = dc.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
self.plotIt = False
try:
from pymatsolver import Pardiso
self.Solver = Pardiso
except ImportError:
self.Solver = SolverLU
def setUp(self):
cs = 12.5
npad = 2
hx = [(cs, npad, -1.3), (cs, 21), (cs, npad, 1.3)]
hy = [(cs, npad, -1.3), (cs, 21), (cs, npad, 1.3)]
hz = [(cs, npad, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy, hz], x0="CCN")
x = mesh.vectorCCx[(mesh.vectorCCx > -80.0) & (mesh.vectorCCx < 80.0)]
y = mesh.vectorCCy[(mesh.vectorCCy > -80.0) & (mesh.vectorCCy < 80.0)]
Aloc = np.r_[-100.0, 0.0, 0.0]
Bloc = np.r_[100.0, 0.0, 0.0]
M = utils.ndgrid(x - 12.5, y, np.r_[0.0])
N = utils.ndgrid(x + 12.5, y, np.r_[0.0])
radius = 50.0
xc = np.r_[0.0, 0.0, -100]
blkind = utils.model_builder.getIndicesSphere(xc, radius, mesh.gridCC)
sigmaInf = np.ones(mesh.nC) * 1e-2
eta = np.zeros(mesh.nC)
eta[blkind] = 0.1
sigma0 = sigmaInf * (1.0 - eta)
rx = dc.receivers.Dipole(M, N)
src = dc.sources.Dipole([rx], Aloc, Bloc)
surveyDC = dc.survey.Survey([src])
self.surveyDC = surveyDC
self.mesh = mesh
self.sigmaInf = sigmaInf
self.sigma0 = sigma0
self.src = src
self.eta = eta
def setUp(self):
npad = 10
cs = 12.5
hx = [(cs, npad, -1.4), (cs, 61), (cs, npad, 1.4)]
hy = [(cs, npad, -1.4), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = mesh.cell_centers_x[
np.logical_and(mesh.cell_centers_x > -150, mesh.cell_centers_x < 250)
]
M = utils.ndgrid(x, np.r_[0.0])
N = utils.ndgrid(x + 12.5 * 4, np.r_[0.0])
A0loc = np.r_[-200, 0.0]
A1loc = np.r_[-250, 0.0]
rx = dc.receivers.Dipole(M, N, data_type="apparent_resistivity")
src0 = dc.sources.Dipole([rx], A0loc, A1loc)
survey = dc.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.sigma_half = sighalf
self.plotIt = False
try:
from pymatsolver import Pardiso
self.solver = Pardiso
except ImportError:
self.solver = SolverLU
def setUp(self):
cs = 25.0
npad = 7
hx = [(cs, npad, -1.3), (cs, 21), (cs, npad, 1.3)]
hy = [(cs, npad, -1.3), (cs, 21), (cs, npad, 1.3)]
hz = [(cs, npad, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy, hz], x0="CCN")
sigma = np.ones(mesh.nC) * 1e-2
x = mesh.vectorCCx[(mesh.vectorCCx > -100) & (mesh.vectorCCx < 100)]
y = mesh.vectorCCy[(mesh.vectorCCy > -100) & (mesh.vectorCCy < 100)]
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])
phiA = analytics.DCAnalytic_Pole_Dipole(Aloc, [M, N],
1e-2,
earth_type="halfspace")
phiB = analytics.DCAnalytic_Pole_Dipole(Bloc, [M, N],
1e-2,
earth_type="halfspace")
data_ana = phiA - phiB
rx = dc.receivers.Dipole(M, N)
src = dc.sources.Dipole([rx], Aloc, Bloc)
survey = dc.survey.Survey([src])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
def setUp(self):
cs = 12.5
hx = [(cs, 7, -1.3), (cs, 61), (cs, 7, 1.3)]
hy = [(cs, 7, -1.3), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = np.linspace(-135, 250.0, 20)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
N = utils.ndgrid(x + 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
A1loc = np.r_[-130, 0.0]
rx = dc.receivers.Dipole(M, N, data_type="apparent_resistivity")
src0 = dc.sources.Dipole([rx], A0loc, A1loc)
survey = dc.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.sigma_half = sighalf
self.plotIt = False
try:
from pymatsolver import Pardiso
self.Solver = Pardiso
except ImportError:
self.Solver = SolverLU
def getSlices(self,
mesh,
vec,
itime,
normal="Z",
loc=0.0,
isz=False,
isy=False):
VEC = vec[:, itime].reshape((mesh.nC, 3), order="F")
if normal == "Z":
ind = np.argmin(abs(mesh.vectorCCz - loc))
vx = VEC[:, 0].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, :, ind]
vy = VEC[:, 1].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, :, ind]
vz = VEC[:, 2].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, :, ind]
xy = utils.ndgrid(mesh.vectorCCx, mesh.vectorCCy)
if isz:
return utils.mkvc(vz), xy
else:
return np.c_[utils.mkvc(vx), utils.mkvc(vy)], xy
elif normal == "Y":
ind = np.argmin(abs(mesh.vectorCCx - loc))
vx = VEC[:, 0].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, ind, :]
vy = VEC[:, 1].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, ind, :]
vz = VEC[:, 2].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[:, ind, :]
xz = utils.ndgrid(mesh.vectorCCx, mesh.vectorCCz)
if isz:
return utils.mkvc(vz), xz
elif isy:
return utils.mkvc(vy), xz
else:
return np.c_[utils.mkvc(vx), utils.mkvc(vz)], xz
elif normal == "X":
ind = np.argmin(abs(mesh.vectorCCy - loc))
vx = VEC[:, 0].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[ind, :, :]
vy = VEC[:, 1].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[ind, :, :]
vz = VEC[:, 2].reshape((mesh.nCx, mesh.nCy, mesh.nCz),
order="F")[ind, :, :]
yz = utils.ndgrid(mesh.vectorCCy, mesh.vectorCCz)
if isz:
return utils.mkvc(vy), yz
elif isy:
return utils.mkvc(vy), yz
else:
return np.c_[utils.mkvc(vy), utils.mkvc(vz)], yz
def setUp(self):
cs = 12.5
hx = [(cs, 7, -1.3), (cs, 61), (cs, 7, 1.3)]
hy = [(cs, 7, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy], x0="CN")
# x = np.linspace(-200, 200., 20)
x = np.linspace(-200, 200.0, 2)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
N = utils.ndgrid(x + 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
A1loc = np.r_[-130, 0.0]
B0loc = np.r_[-130, 0.0]
B1loc = np.r_[-110, 0.0]
rx = dc.Rx.Dipole(M, N)
src0 = dc.Src.Dipole([rx], A0loc, B0loc)
src1 = dc.Src.Dipole([rx], A1loc, B1loc)
survey = ip.Survey([src0, src1])
sigma = np.ones(mesh.nC) * 1.0
problem = ip.Simulation2DCellCentered(
mesh,
survey=survey,
sigma=sigma,
etaMap=maps.IdentityMap(mesh),
verbose=False,
)
mSynth = np.ones(mesh.nC) * 0.1
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
def setUp(self):
print("\n ---- Testing {} ---- \n".format(self.formulation))
cs = 12.5
hx = [(cs, 2, -1.3), (cs, 61), (cs, 2, 1.3)]
hy = [(cs, 2, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy], x0="CN")
x = np.linspace(-135, 250.0, 20)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
N = utils.ndgrid(x + 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
A1loc = np.r_[-130, 0.0]
# rxloc = [np.c_[M, np.zeros(20)], np.c_[N, np.zeros(20)]]
rx1 = dc.receivers.Dipole(M, N)
rx2 = dc.receivers.Dipole(M, N, data_type="apparent_resistivity")
src0 = dc.sources.Pole([rx1, rx2], A0loc)
src1 = dc.sources.Pole([rx1, rx2], A1loc)
survey = dc.survey.Survey([src0, src1])
survey.set_geometric_factor()
simulation = getattr(dc, self.formulation)(
mesh,
rhoMap=maps.IdentityMap(mesh),
storeJ=self.storeJ,
solver=Solver,
survey=survey,
bc_type=self.bc_type,
)
mSynth = np.ones(mesh.nC) * 1.0
data = simulation.make_synthetic_data(mSynth, add_noise=True)
# Now set up the problem to do some minimization
dmis = data_misfit.L2DataMisfit(simulation=simulation, data=data)
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=1e0)
inv = inversion.BaseInversion(invProb)
self.inv = inv
self.reg = reg
self.p = simulation
self.mesh = mesh
self.m0 = mSynth
self.survey = survey
self.dmis = dmis
self.data = data
def setUp(self):
mesh = discretize.TensorMesh([np.ones(n) * 5 for n in [10, 11, 12]],
[0, 0, -30])
x = np.linspace(5, 10, 3)
XYZ = utils.ndgrid(x, x, np.r_[0.0])
srcLoc = np.r_[0, 0, 0.0]
rxList0 = survey.BaseRx(XYZ)
Src0 = survey.BaseSrc([rxList0], location=srcLoc)
rxList1 = survey.BaseRx(XYZ)
Src1 = survey.BaseSrc([rxList1], location=srcLoc)
rxList2 = survey.BaseRx(XYZ)
Src2 = survey.BaseSrc([rxList2], location=srcLoc)
rxList3 = survey.BaseRx(XYZ)
Src3 = survey.BaseSrc([rxList3], location=srcLoc)
Src4 = survey.BaseSrc([rxList0, rxList1, rxList2, rxList3],
location=srcLoc)
source_list = [Src0, Src1, Src2, Src3, Src4]
mysurvey = survey.BaseSurvey(source_list=source_list)
sim = simulation.BaseTimeSimulation(mesh,
time_steps=[(10.0, 3), (20.0, 2)],
survey=mysurvey)
self.F = fields.TimeFields(simulation=sim,
knownFields={
"phi": "CC",
"e": "E",
"b": "F"
})
self.Src0 = Src0
self.Src1 = Src1
self.mesh = mesh
self.XYZ = XYZ
def setUp(self):
mesh = discretize.TensorMesh([np.ones(n) * 5 for n in [10, 11, 12]],
[0, 0, -30])
x = np.linspace(5, 10, 3)
XYZ = utils.ndgrid(x, x, np.r_[0.0])
srcLoc = np.r_[0, 0, 0.0]
rxList0 = survey.BaseRx(XYZ)
Src0 = survey.BaseSrc([rxList0], location=srcLoc)
rxList1 = survey.BaseRx(XYZ)
Src1 = survey.BaseSrc([rxList1], location=srcLoc)
rxList2 = survey.BaseRx(XYZ)
Src2 = survey.BaseSrc([rxList2], location=srcLoc)
rxList3 = survey.BaseRx(XYZ)
Src3 = survey.BaseSrc([rxList3], location=srcLoc)
Src4 = survey.BaseSrc([rxList0, rxList1, rxList2, rxList3],
location=srcLoc)
source_list = [Src0, Src1, Src2, Src3, Src4]
mysurvey = survey.BaseSurvey(source_list=source_list)
sim = simulation.BaseSimulation(mesh=mesh, survey=mysurvey)
self.F = fields.Fields(
sim,
knownFields={"e": "E"},
aliasFields={
"b": ["e", "F", (lambda e, ind: self.F.mesh.edgeCurl * e)]
},
)
self.Src0 = Src0
self.Src1 = Src1
self.mesh = mesh
self.XYZ = XYZ
self.simulation = sim
def setUp(self):
# Note: Pole-Pole requires bigger boundary to obtain good accuracy.
# One can use greater padding rate. Here 1.5 is used.
cs = 12.5
hx = [(cs, 7, -1.5), (cs, 61), (cs, 7, 1.5)]
hy = [(cs, 7, -1.5), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = np.linspace(0, 250.0, 20)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
rxloc = np.c_[M, np.zeros(20)]
data_ana = analytics.DCAnalytic_Pole_Pole(np.r_[A0loc, 0.0],
rxloc,
sighalf,
earth_type="halfspace")
rx = dc.receivers.Pole(M)
src0 = dc.sources.Pole([rx], A0loc)
survey = dc.survey.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
try:
from pymatsolver import PardisoSolver
self.Solver = PardisoSolver
except ImportError:
self.Solver = SolverLU
def test_Transect(self, plotIt=plotIt):
for src in self.prb.survey.source_list:
print(" --- testing {} --- ".format(src.__class__.__name__))
x = np.linspace(-55, 55, 12)
XYZ = utils.ndgrid(x, np.r_[0], np.r_[0])
P = self.mesh.getInterpolationMat(XYZ, "Fz")
ana = mu_0 * np.imag(
analytics.FDEM.hzAnalyticDipoleF(x, src.frequency, self.sig))
num = P * np.imag(self.u[src, "b"])
diff = np.linalg.norm(num - ana)
if plotIt:
import matplotlib.pyplot as plt
plt.plot(x, np.log10(np.abs(num)))
plt.plot(x, np.log10(np.abs(ana)), "r")
plt.plot(x, diff, "g")
plt.show()
norm_num = np.linalg.norm(num)
norm_ana = np.linalg.norm(ana)
tol = tol_Transect * (norm_num + norm_ana) / 2.0
passed = diff < tol
print("analytic: {}, numeric {}, difference {} < tolerance {} ? "
" {}".format(norm_ana, norm_num, diff, tol, passed))
self.assertTrue(passed)
def setUp(self):
mesh = discretize.TensorMesh([np.ones(n) * 5 for n in [10, 11, 12]],
[0, 0, -30])
x = np.linspace(5, 10, 3)
XYZ = utils.ndgrid(x, x, np.r_[0.0])
srcLoc = np.r_[0, 0, 0.0]
rxList0 = survey.BaseRx(XYZ)
Src0 = survey.BaseSrc(receiver_list=[rxList0], location=srcLoc)
rxList1 = survey.BaseRx(XYZ)
Src1 = survey.BaseSrc(receiver_list=[rxList1], location=srcLoc)
rxList2 = survey.BaseRx(XYZ)
Src2 = survey.BaseSrc(receiver_list=[rxList2], location=srcLoc)
rxList3 = survey.BaseRx(XYZ)
Src3 = survey.BaseSrc(receiver_list=[rxList3], location=srcLoc)
Src4 = survey.BaseSrc(
receiver_list=[rxList0, rxList1, rxList2, rxList3],
location=srcLoc)
source_list = [Src0, Src1, Src2, Src3, Src4]
mysurvey = survey.BaseSurvey(source_list=source_list)
sim = simulation.BaseTimeSimulation(mesh,
time_steps=[(10.0, 3), (20.0, 2)],
survey=mysurvey)
def alias(b, srcInd, timeInd):
return self.F.mesh.edgeCurl.T * b + timeInd
self.F = fields.TimeFields(sim,
knownFields={"b": "F"},
aliasFields={"e": ["b", "E", alias]})
self.Src0 = Src0
self.Src1 = Src1
self.mesh = mesh
self.XYZ = XYZ
self.simulation = sim
def setUp(self):
cs = 25.0
hx = [(cs, 7, -1.5), (cs, 21), (cs, 7, 1.5)]
hy = [(cs, 7, -1.5), (cs, 21), (cs, 7, 1.5)]
hz = [(cs, 7, -1.5), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy, hz], x0="CCN")
sigma = np.ones(mesh.nC) * 1e-2
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]
M = utils.ndgrid(x, y, np.r_[0.0])
phiA = analytics.DCAnalytic_Pole_Pole(Aloc,
M,
1e-2,
earth_type="halfspace")
data_ana = phiA
rx = dc.receivers.Pole(M)
src = dc.sources.Pole([rx], Aloc)
survey = dc.survey.Survey([src])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
def setUp(self):
mesh = Mesh.TensorMesh([30, 30], x0=[-0.5, -1.0])
sigma = np.ones(mesh.nC)
model = np.log(sigma)
prob = DC.Problem3D_CC(mesh, rhoMap=Maps.ExpMap(mesh))
rx = DC.Rx.Pole(Utils.ndgrid([mesh.vectorCCx, np.r_[mesh.vectorCCy.max()]]))
src = DC.Src.Dipole(
[rx], np.r_[-0.25, mesh.vectorCCy.max()], np.r_[0.25, mesh.vectorCCy.max()]
)
survey = DC.Survey([src])
prob.pair(survey)
self.std = 0.01
survey.std = self.std
dobs = survey.makeSyntheticData(model)
self.eps = 1e-8 * np.min(np.abs(dobs))
survey.eps = self.eps
dmis = DataMisfit.l2_DataMisfit(survey)
self.model = model
self.mesh = mesh
self.survey = survey
self.prob = prob
self.dobs = dobs
self.dmis = dmis
def plot_data_inversion(self, ii, pred, fixed=False):
titles = ["Observed", "Predicted", "Normalized misfit"]
x = np.arange(10) + 1
y = np.arange(10) + 1
xy = utils.ndgrid(x, y)
fig, axs = plt.subplots(1, 3, figsize=(10, 3))
if fixed:
clim = (self.dobs.min(), self.dobs.max())
else:
clim = None
out = utils.plot2Ddata(xy, self.dobs, ax=axs[0], clim=clim)
plt.colorbar(out[0], ax=axs[0], fraction=0.02)
out = utils.plot2Ddata(xy, pred[ii], ax=axs[1], clim=clim)
plt.colorbar(out[0], ax=axs[1], fraction=0.02)
out = utils.plot2Ddata(xy, (pred[ii] - self.dobs) / self.uncertainty,
ax=axs[2],
clim=(-3, 3))
plt.colorbar(out[0], ax=axs[2], fraction=0.02, ticks=[-2, -1, 0, 1, 2])
for ii, ax in enumerate(axs):
ax.set_aspect(1)
ax.set_title(titles[ii])
ax.set_xlabel("Rx")
ax.set_ylabel("Tx")
plt.tight_layout()
plt.show()
def test_ndgrid_2D(self):
XY = ndgrid([self.a, self.b])
X1_test = np.array([1, 2, 3, 1, 2, 3])
X2_test = np.array([1, 1, 1, 2, 2, 2])
self.assertTrue(np.all(XY[:, 0] == X1_test))
self.assertTrue(np.all(XY[:, 1] == X2_test))
def setUp(self):
print("\nTesting Transect for analytic")
cs = 10.0
ncx, ncy, ncz = 10, 10, 10
npad = 5
freq = 1e2
hx = [(cs, npad, -1.3), (cs, ncx), (cs, npad, 1.3)]
hy = [(cs, npad, -1.3), (cs, ncy), (cs, npad, 1.3)]
hz = [(cs, npad, -1.3), (cs, ncz), (cs, npad, 1.3)]
mesh = discretize.TensorMesh([hx, hy, hz], "CCC")
x = np.linspace(-10, 10, 5)
XYZ = utils.ndgrid(x, np.r_[0], np.r_[0])
rxList = fdem.Rx.PointElectricField(XYZ,
orientation="x",
component="imag")
SrcList = [
fdem.Src.MagDipole([rxList],
location=np.r_[0.0, 0.0, 0.0],
frequency=freq),
fdem.Src.CircularLoop(
[rxList],
location=np.r_[0.0, 0.0, 0.0],
frequency=freq,
radius=np.sqrt(1.0 / np.pi),
),
# fdem.Src.MagDipole_Bfield(
# [rxList], loc=np.r_[0., 0., 0.],
# freq=freq
# ), # less accurate
]
survey = fdem.Survey(SrcList)
sig = 1e-1
sigma = np.ones(mesh.nC) * sig
sigma[mesh.gridCC[:, 2] > 0] = 1e-8
prb = fdem.Simulation3DMagneticFluxDensity(mesh, sigma=sigma)
prb.pair(survey)
try:
from pymatsolver import Pardiso
prb.Solver = Pardiso
except ImportError:
prb.Solver = SolverLU
self.prb = prb
self.mesh = mesh
self.sig = sig
print(" starting solve ...")
u = self.prb.fields()
print(" ... done")
self.u = u
def setUp(self):
mesh = discretize.TensorMesh([30, 30], x0=[-0.5, -1.0])
sigma = np.random.rand(mesh.nC)
model = np.log(sigma)
# prob = DC.Simulation3DCellCentered(mesh, rhoMap=maps.ExpMap(mesh))
# prob1 = DC.Simulation3DCellCentered(mesh, rhoMap=maps.ExpMap(mesh))
rx = DC.Rx.Pole(utils.ndgrid([mesh.vectorCCx, np.r_[mesh.vectorCCy.max()]]))
rx1 = DC.Rx.Pole(utils.ndgrid([mesh.vectorCCx, np.r_[mesh.vectorCCy.min()]]))
src = DC.Src.Dipole(
[rx], np.r_[-0.25, mesh.vectorCCy.max()], np.r_[0.25, mesh.vectorCCy.max()]
)
src1 = DC.Src.Dipole(
[rx1], np.r_[-0.25, mesh.vectorCCy.max()], np.r_[0.25, mesh.vectorCCy.max()]
)
survey = DC.Survey([src])
simulation0 = DC.simulation.Simulation3DCellCentered(
mesh=mesh, survey=survey, rhoMap=maps.ExpMap(mesh)
)
survey1 = DC.Survey([src1])
simulation1 = DC.simulation.Simulation3DCellCentered(
mesh=mesh, survey=survey1, rhoMap=maps.ExpMap(mesh)
)
dobs0 = simulation0.make_synthetic_data(model)
dobs1 = simulation1.make_synthetic_data(model)
self.mesh = mesh
self.model = model
self.survey0 = survey
self.sim0 = simulation0
self.survey1 = survey1
self.sim1 = simulation1
# self.dmis0 = data_misfit.L2DataMisfit(self.survey0)
self.dmis0 = data_misfit.L2DataMisfit(data=dobs0, simulation=simulation0)
self.dmis1 = data_misfit.L2DataMisfit(data=dobs1, simulation=simulation1)
self.dmiscombo = self.dmis0 + self.dmis1
def setUp(self):
cs = 12.5
hx = [(cs, 7, -1.3), (cs, 61), (cs, 7, 1.3)]
hy = [(cs, 7, -1.3), (cs, 20)]
mesh = discretize.TensorMesh([hx, hy], x0="CN")
x = np.linspace(-200, 200.0, 20)
M = utils.ndgrid(x - 12.5, np.r_[0.0])
N = utils.ndgrid(x + 12.5, np.r_[0.0])
A0loc = np.r_[-150, 0.0]
A1loc = np.r_[-130, 0.0]
B0loc = np.r_[-130, 0.0]
B1loc = np.r_[-110, 0.0]
rx = dc.Rx.Dipole(M, N)
src0 = dc.Src.Dipole([rx], A0loc, B0loc)
src1 = dc.Src.Dipole([rx], A1loc, B1loc)
src0_ip = dc.Src.Dipole([rx], A0loc, B0loc)
src1_ip = dc.Src.Dipole([rx], A1loc, B1loc)
source_lists = [src0, src1]
source_lists_ip = [src0_ip, src1_ip]
surveyDC = dc.Survey([src0, src1])
sigmaInf = np.ones(mesh.nC) * 1.0
blkind = utils.model_builder.getIndicesSphere(np.r_[0, -150], 40,
mesh.gridCC)
eta = np.zeros(mesh.nC)
eta[blkind] = 0.1
sigma0 = sigmaInf * (1.0 - eta)
self.surveyDC = surveyDC
self.mesh = mesh
self.sigmaInf = sigmaInf
self.sigma0 = sigma0
self.source_lists = source_lists
self.source_lists_ip = source_lists_ip
self.eta = eta
def setUp(self):
npad = 10
cs = 12.5
hx = [(cs, npad, -1.4), (cs, 61), (cs, npad, 1.4)]
hy = [(cs, npad, -1.4), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = mesh.cell_centers_x[
np.logical_and(mesh.cell_centers_x > -150, mesh.cell_centers_x < 250)
]
M = utils.ndgrid(x, np.r_[0.0])
N = utils.ndgrid(x + 12.5 * 4, np.r_[0.0])
A0loc = np.r_[-200, 0.0]
A1loc = np.r_[-250, 0.0]
rxloc = [np.c_[M, np.zeros(x.size)], np.c_[N, np.zeros(x.size)]]
data_ana_A = analytics.DCAnalytic_Pole_Dipole(
np.r_[A0loc, 0.0], rxloc, sighalf, earth_type="halfspace"
)
data_ana_b = analytics.DCAnalytic_Pole_Dipole(
np.r_[A1loc, 0.0], rxloc, sighalf, earth_type="halfspace"
)
data_ana = data_ana_A - data_ana_b
rx = dc.receivers.Dipole(M, N)
src0 = dc.sources.Dipole([rx], A0loc, A1loc)
survey = dc.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
self.plotIt = False
try:
from pymatsolver import Pardiso
self.solver = Pardiso
except ImportError:
self.solver = SolverLU
def setUp(self):
mesh = discretize.TensorMesh([np.ones(n) * 5 for n in [10, 11, 12]],
[0, 0, -30])
x = np.linspace(5, 10, 3)
XYZ = utils.ndgrid(x, x, np.r_[0.0])
srcLoc = np.r_[0.0, 0.0, 0.0]
receiver_list0 = survey.BaseRx(XYZ)
Src0 = survey.BaseSrc([receiver_list0], location=srcLoc)
receiver_list1 = survey.BaseRx(XYZ)
Src1 = survey.BaseSrc([receiver_list1], location=srcLoc)
receiver_list2 = survey.BaseRx(XYZ)
Src2 = survey.BaseSrc([receiver_list2], location=srcLoc)
receiver_list3 = survey.BaseRx(XYZ)
Src3 = survey.BaseSrc([receiver_list3], location=srcLoc)
Src4 = survey.BaseSrc(
[receiver_list0, receiver_list1, receiver_list2, receiver_list3],
location=srcLoc,
)
source_list = [Src0, Src1, Src2, Src3, Src4]
mysurvey = survey.BaseSurvey(source_list=source_list)
sim = simulation.BaseSimulation(mesh=mesh, survey=mysurvey)
self.D = data.Data(mysurvey)
self.F = fields.Fields(
sim,
knownFields={
"phi": "CC",
"e": "E",
"b": "F"
},
dtype={
"phi": float,
"e": complex,
"b": complex
},
)
self.Src0 = Src0
self.Src1 = Src1
self.mesh = mesh
self.XYZ = XYZ
self.simulation = sim
def plot_survey_data(self, percentage, floor, seed, add_noise, plot_type,
update):
self._percentage = percentage
self._floor = floor
self._seed = seed
self._dobs = self.add_noise()
self._data_prop.dobs = self._dobs.copy()
fig, axs = plt.subplots(1, 2, figsize=(8, 4))
out = self.mesh_prop.plotImage(1.0 / self.slowness_prop, ax=axs[0])
cb = plt.colorbar(out[0], ax=axs[0], fraction=0.02)
cb.set_label("Velocity (m/s)")
self.survey_prop.plot(ax=axs[0])
axs[0].set_title("Survey")
axs[0].set_xlabel("x (m)")
axs[0].set_ylabel("z (m)")
x = np.arange(10) + 1
y = np.arange(10) + 1
xy = utils.ndgrid(x, y)
if plot_type == "tx_rx_plane":
if add_noise:
out = utils.plot2Ddata(xy, self.dobs, ax=axs[1])
else:
out = utils.plot2Ddata(xy, self.pred, ax=axs[1])
axs[1].set_xlabel("Rx")
axs[1].set_ylabel("Tx")
axs[1].set_xticks(x)
axs[1].set_yticks(y)
cb = plt.colorbar(out[0], ax=axs[1], fraction=0.02)
cb.set_label("Traveltime (s)")
for ax in axs:
ax.set_aspect(1)
else:
if add_noise:
out = axs[1].hist(self.pred, edgecolor="k")
else:
out = axs[1].hist(self.dobs, edgecolor="k")
axs[1].set_ylabel("Count")
axs[1].set_xlabel("Travel time (s)")
axs[0].set_aspect(1)
plt.tight_layout()
plt.show()
def setUp(self):
mesh = discretize.TensorMesh([np.ones(n) * 5 for n in [10, 11, 12]],
[0, 0, -30])
x = np.linspace(5, 10, 3)
XYZ = utils.ndgrid(x, x, np.r_[0.0])
srcLoc = np.r_[0, 0, 0.0]
rxList0 = survey.BaseRx(XYZ)
Src0 = survey.BaseSrc([rxList0], location=srcLoc)
rxList1 = survey.BaseRx(XYZ)
Src1 = survey.BaseSrc([rxList1], location=srcLoc)
rxList2 = survey.BaseRx(XYZ)
Src2 = survey.BaseSrc([rxList2], location=srcLoc)
rxList3 = survey.BaseRx(XYZ)
Src3 = survey.BaseSrc([rxList3], location=srcLoc)
Src4 = survey.BaseSrc([rxList0, rxList1, rxList2, rxList3],
location=srcLoc)
srcList = [Src0, Src1, Src2, Src3, Src4]
mysurvey = survey.BaseSurvey(source_list=srcList)
self.D = data.Data(mysurvey)
def test_ndgrid_3D(self):
XYZ = ndgrid([self.a, self.b, self.c])
X1_test = np.array([
1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1,
2, 3
])
X2_test = np.array([
1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2,
2, 2
])
X3_test = np.array([
1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4,
4, 4
])
self.assertTrue(np.all(XYZ[:, 0] == X1_test))
self.assertTrue(np.all(XYZ[:, 1] == X2_test))
self.assertTrue(np.all(XYZ[:, 2] == X3_test))
def setUp(self):
cs = 10
nc = 20
npad = 10
mesh = discretize.CylMesh([
[(cs, nc), (cs, npad, 1.3)],
np.r_[2 * np.pi],
[(cs, npad, -1.3), (cs, nc), (cs, npad, 1.3)],
])
mesh.x0 = np.r_[0.0, 0.0, -mesh.hz[:npad + nc].sum()]
# receivers
rx_x = np.linspace(10, 200, 20)
rx_z = np.r_[-5]
rx_locs = utils.ndgrid([rx_x, np.r_[0], rx_z])
rx_list = [
dc.receivers.BaseRx(rx_locs, projField="e", orientation="x")
]
# sources
src_a = np.r_[0.0, 0.0, -5.0]
src_b = np.r_[55.0, 0.0, -5.0]
src_list = [
dc.sources.Dipole(rx_list, locationA=src_a, locationB=src_b)
]
self.mesh = mesh
self.survey = dc.survey.Survey(src_list)
self.sigma_map = maps.ExpMap(mesh) * maps.InjectActiveCells(
mesh, mesh.gridCC[:, 2] <= 0, np.log(1e-8))
self.prob = dc.simulation.Simulation3DCellCentered(
mesh=mesh,
survey=self.survey,
sigmaMap=self.sigma_map,
Solver=Pardiso,
bc_type="Dirichlet",
)
def setUp(self):
# Note: Pole-Pole requires bigger boundary to obtain good accuracy.
# One can use greater padding rate. Here 2 is used.
npad = 10
cs = 12.5
hx = [(cs, npad, -2), (cs, 61), (cs, npad, 2)]
hy = [(cs, npad, -2), (cs, 20)]
mesh = TensorMesh([hx, hy], x0="CN")
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
x = mesh.cell_centers_x[
np.logical_and(mesh.cell_centers_x > -150, mesh.cell_centers_x < 250)
]
M = utils.ndgrid(x, np.r_[0.0])
# N = utils.ndgrid(x + 12.5*4, np.r_[0.0])
A0loc = np.r_[-200, 0.0]
# A1loc = np.r_[-250, 0.0]
rxloc = np.c_[M, np.zeros(x.size)]
data_ana = analytics.DCAnalytic_Pole_Pole(
np.r_[A0loc, 0.0], rxloc, sighalf, earth_type="halfspace"
)
rx = dc.receivers.Pole(M)
src0 = dc.sources.Pole([rx], A0loc)
survey = dc.survey.Survey([src0])
self.survey = survey
self.mesh = mesh
self.sigma = sigma
self.data_ana = data_ana
try:
from pymatsolver import PardisoSolver
self.solver = PardisoSolver
except ImportError:
self.solver = SolverLU
def simulate_dipole(
self,
component,
target,
inclination,
declination,
length,
dx,
moment,
depth,
profile,
fixed_scale,
show_halfwidth,
):
self.component = component
self.target = target
self.inclination = inclination
self.declination = declination
self.length = length
self.dx = dx
self.moment = moment
self.depth = depth
self.profile = profile
self.fixed_scale = fixed_scale
self.show_halfwidth = show_halfwidth
nT = 1e9
nx = ny = int(length / dx)
hx = np.ones(nx) * dx
hy = np.ones(ny) * dx
self.mesh = TensorMesh((hx, hy), "CC")
z = np.r_[1.0]
orientation = self.id_to_cartesian(inclination, declination)
if self.target == "Dipole":
md = em.static.MagneticDipoleWholeSpace(location=np.r_[0, 0,
-depth],
orientation=orientation,
moment=moment)
xyz = utils.ndgrid(self.mesh.vectorCCx, self.mesh.vectorCCy, z)
b_vec = md.magnetic_flux_density(xyz)
elif self.target == "Monopole (+)":
md = em.static.MagneticPoleWholeSpace(location=np.r_[0, 0, -depth],
orientation=orientation,
moment=moment)
xyz = utils.ndgrid(self.mesh.vectorCCx, self.mesh.vectorCCy, z)
b_vec = md.magnetic_flux_density(xyz)
elif self.target == "Monopole (-)":
md = em.static.MagneticPoleWholeSpace(location=np.r_[0, 0, -depth],
orientation=orientation,
moment=moment)
xyz = utils.ndgrid(self.mesh.vectorCCx, self.mesh.vectorCCy, z)
b_vec = -md.magnetic_flux_density(xyz)
# Project to the direction of earth field
if component == "Bt":
rx_orientation = orientation.copy()
elif component == "Bg":
rx_orientation = orientation.copy()
xyz_up = utils.ndgrid(self.mesh.vectorCCx, self.mesh.vectorCCy,
z + 1.0)
b_vec -= md.magnetic_flux_density(xyz_up)
elif component == "Bx":
rx_orientation = self.id_to_cartesian(0, 0)
elif component == "By":
rx_orientation = self.id_to_cartesian(0, 90)
elif component == "Bz":
rx_orientation = self.id_to_cartesian(90, 0)
self.data = self.dot_product(b_vec, rx_orientation) * nT
# Compute profile
if (profile == "North") or (profile == "None"):
self.xy_profile = np.c_[np.zeros(self.mesh.nCx),
self.mesh.vectorCCx]
elif profile == "East":
self.xy_profile = np.c_[self.mesh.vectorCCx,
np.zeros(self.mesh.nCx)]
self.inds_profile = utils.closestPoints(self.mesh, self.xy_profile)
self.data_profile = self.data[self.inds_profile]
def simulate_prism(
self,
component,
inclination,
declination,
length,
dx,
B0,
kappa,
depth,
profile,
fixed_scale,
show_halfwidth,
prism_dx,
prism_dy,
prism_dz,
prism_inclination,
prism_declination,
):
self.component = component
self.inclination = -inclination # -ve accounts for LH modeling in SimPEG
self.declination = declination
self.length = length
self.dx = dx
self.B0 = B0
self.kappa = kappa
self.depth = depth
self.profile = profile
self.fixed_scale = fixed_scale
self.show_halfwidth = show_halfwidth
# prism parameter
self.prism = self.get_prism(
prism_dx,
prism_dy,
prism_dz,
0,
0,
-depth,
prism_inclination,
prism_declination,
)
nx = ny = int(length / dx)
hx = np.ones(nx) * dx
hy = np.ones(ny) * dx
self.mesh = TensorMesh((hx, hy), "CC")
z = np.r_[1.0]
B = np.r_[B0, -inclination,
declination] # -ve accounts for LH modeling in SimPEG
# Project to the direction of earth field
if component == "Bt":
uType = "tf"
elif component == "Bx":
uType = "bx"
elif component == "By":
uType = "by"
elif component == "Bz":
uType = "bz"
xyz = utils.ndgrid(self.mesh.vectorCCx, self.mesh.vectorCCy, z)
out = createMagSurvey(np.c_[xyz, np.ones(self.mesh.nC)], B)
self.survey = out[0]
self.dobs = out[1]
self.sim = Simulation()
self.sim.prism = self.prism
self.sim.survey = self.survey
self.sim.susc = kappa
self.sim.uType, self.sim.mType = uType, "induced"
self.data = self.sim.fields()[0]
# Compute profile
if (profile == "North") or (profile == "None"):
self.xy_profile = np.c_[np.zeros(self.mesh.nCx),
self.mesh.vectorCCx]
elif profile == "East":
self.xy_profile = np.c_[self.mesh.vectorCCx,
np.zeros(self.mesh.nCx)]
self.inds_profile = utils.closestPoints(self.mesh, self.xy_profile)
self.data_profile = self.data[self.inds_profile]
np.mean(block_z),
np.diff(block_z),
np.mean(block_x),
np.diff(block_x),
np.mean(block_y),
np.diff(block_y), ]
# source
src_loc = np.r_[0.0, 0.0, 0.0]
freq = 10
# receivers
rx_x = np.linspace(-175.0, 175.0, 8)
rx_y = rx_x.copy()
rx_z = np.r_[175.0]
rx_locs = utils.ndgrid(rx_x, rx_y, rx_z)
# mesh
csx, ncx, npadx = 25.0, 16, 10
csz, ncz, npadz = 25.0, 8, 10
pf = 1.5
# primary mesh
hx = [(csx, ncx), (csx, npadx, pf)]
hz = [(csz, npadz, -pf), (csz, ncz), (csz, npadz, pf)]
meshp = discretize.CylMesh([hx, 1.0, hz], x0="0CC")
# secondary mesh
h = [(csz, npadz - 4, -pf), (csz, ncz), (csz, npadz - 4, pf)]
meshs = discretize.TensorMesh(3 * [h], x0="CCC")
