def run(plotIt=False):
cs = 25.
hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
hz = [(cs,7, -1.3),(cs,20)]
mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
sighalf = 1e-2
sigma = np.ones(mesh.nC)*sighalf
xtemp = np.linspace(-150, 150, 21)
ytemp = np.linspace(-150, 150, 21)
xyz_rxP = Utils.ndgrid(xtemp-10., ytemp, np.r_[0.])
xyz_rxN = Utils.ndgrid(xtemp+10., ytemp, np.r_[0.])
xyz_rxM = Utils.ndgrid(xtemp, ytemp, np.r_[0.])
# if plotIt:
# fig, ax = plt.subplots(1,1, figsize = (5,5))
# mesh.plotSlice(sigma, grid=True, ax = ax)
# ax.plot(xyz_rxP[:,0],xyz_rxP[:,1], 'w.')
# ax.plot(xyz_rxN[:,0],xyz_rxN[:,1], 'r.', ms = 3)
rx = DC.RxDipole(xyz_rxP, xyz_rxN)
src = DC.SrcDipole([rx], [-200, 0, -12.5], [+200, 0, -12.5])
survey = DC.SurveyDC([src])
problem = DC.ProblemDC_CC(mesh)
problem.pair(survey)
try:
from pymatsolver import MumpsSolver
problem.Solver = MumpsSolver
except Exception, e:
pass
def test_IPforward(self):
cs = 12.5
nc = 200 / cs + 1
hx = [(cs, 7, -1.3), (cs, nc), (cs, 7, 1.3)]
hy = [(cs, 7, -1.3), (cs, int(nc / 2 + 1)), (cs, 7, 1.3)]
hz = [(cs, 7, -1.3), (cs, int(nc / 2 + 1))]
mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')
sighalf = 1e-2
sigma = np.ones(mesh.nC) * sighalf
p0 = np.r_[-50., 50., -50.]
p1 = np.r_[50., -50., -150.]
blk_ind = Utils.ModelBuilder.getIndicesBlock(p0, p1, mesh.gridCC)
sigma[blk_ind] = 1e-3
eta = np.zeros_like(sigma)
eta[blk_ind] = 0.1
sigmaInf = sigma.copy()
sigma0 = sigma * (1 - eta)
nElecs = 11
x_temp = np.linspace(-100, 100, nElecs)
aSpacing = x_temp[1] - x_temp[0]
y_temp = 0.
xyz = Utils.ndgrid(x_temp, np.r_[y_temp], np.r_[0.])
srcList = DC.Utils.WennerSrcList(nElecs, aSpacing)
survey = DC.SurveyDC(srcList)
imap = Maps.IdentityMap(mesh)
problem = DC.ProblemDC_CC(mesh, mapping=imap)
try:
from pymatsolver import MumpsSolver
solver = MumpsSolver
except ImportError, e:
solver = SolverLU
def setUp(self):
aSpacing = 2.5
nElecs = 10
surveySize = nElecs * aSpacing - aSpacing
cs = surveySize / nElecs / 4
mesh = Mesh.TensorMesh(
[
[(cs, 10, -1.3), (cs, surveySize / cs), (cs, 10, 1.3)],
[(cs, 3, -1.3), (cs, 3, 1.3)],
# [(cs,5, -1.3),(cs,10)]
],
'CN')
srcList = DC.Utils.WennerSrcList(nElecs, aSpacing, in2D=True)
survey = DC.SurveyDC(srcList)
problem = DC.ProblemDC_CC(mesh)
problem.pair(survey)
mSynth = np.ones(mesh.nC)
survey.makeSyntheticData(mSynth)
# Now set up the problem to do some minimization
dmis = DataMisfit.l2_DataMisfit(survey)
reg = Regularization.Tikhonov(mesh)
opt = Optimization.InexactGaussNewton(maxIterLS=20,
maxIter=10,
tolF=1e-6,
tolX=1e-6,
tolG=1e-6,
maxIterCG=6)
invProb = InvProblem.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
alpha=0.75,
vmin=-1e-2,
vmax=1e-2)
cbar = plt.colorbar(im2,
format="$10^{%.1f}$",
fraction=0.04,
orientation="horizontal")
im3 = axs.streamplot(xx,
zz,
np.zeros((mesh2d.nCy, mesh2d.nCx)),
np.zeros((mesh2d.nCy, mesh2d.nCx)),
color='k')
im4 = axs.scatter([], [], c='r', s=200)
im5 = axs.scatter([], [], c='r', s=200)
problem = DC.ProblemDC_CC(mesh)
tinf = np.squeeze(Rx[-1][-1, :3]) + np.array([dl_x, dl_y, 0]) * 10 * a
def animate(ii):
removeStream()
if not re.match(stype, 'pdp'):
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T,
'CC').T * ([-1, 1] / mesh.vol[inds])
else: