def test_map2Dto3D_y(self):
M2 = discretize.TensorMesh([3, 4])
M3 = discretize.TensorMesh([3, 2, 4])
m = np.random.rand(M2.nC)
for m2to3 in [
maps.Surject2Dto3D(M3, normal="Y"),
]:
# m2to3 = maps.Surject2Dto3D(M3, normal='Y')
m = np.arange(m2to3.nP)
self.assertTrue(m2to3.test())
self.assertTrue(m2to3.testVec())
self.assertTrue(
np.all(utils.mkvc((m2to3 * m).reshape(M3.vnC, order="F")[:, 0, :]) == m)
)
###############################################################################
# Mappings
# ---------
#
# Mappings are used to take the inversion model and represent it as electrical
# conductivity on the inversion mesh. We will invert for log-conductivity below
# the surface, fixing the conductivity of the air cells to 1e-8 S/m
# create a 2D mesh that includes air cells
mesh2D = discretize.TensorMesh([mesh.hx, mesh.hz], x0=mesh.x0[[0, 2]])
active_inds = mesh2D.gridCC[:, 1] < 0 # active indices are below the surface
mapping = (
maps.Surject2Dto3D(mesh)
* maps.InjectActiveCells( # populates 3D space from a 2D model
mesh2D, active_inds, sigma_air
)
* maps.ExpMap( # adds air cells
nP=inversion_mesh.nC
) # takes the exponential (log(sigma) --> sigma)
)
###############################################################################
# True Model
# ----------
#
# Create our true model which we will use to generate synthetic data for
m_true = np.log(sigma_deep) * np.ones(inversion_mesh.nC)