def setUp(self):
dh = 1.0
nx = 16
ny = 16
nz = 16
hx = [(dh, nx)]
hy = [(dh, ny)]
hz = [(dh, nz)]
mesh = TreeMesh([hx, hy, hz], "CNN")
mesh.insert_cells([5, 5, 5], [4])
# reg
actv = np.ones(len(mesh), dtype=bool)
# maps
wires = maps.Wires(("m1", mesh.nC), ("m2", mesh.nC))
cross_grad = regularization.CrossGradient(mesh,
wire_map=wires,
indActive=actv)
self.mesh = mesh
self.cross_grad = cross_grad
def setUp(self):
dh = 1.0
nx = 16
ny = 16
nz = 16
hx = [(dh, nx)]
hy = [(dh, ny)]
hz = [(dh, nz)]
mesh = TreeMesh([hx, hy, hz], "CNN")
mesh.insert_cells([5, 5, 5], [4])
# reg
actv = np.ones(len(mesh), dtype=bool)
# maps
wires = maps.Wires(("m1", mesh.nC), ("m2", mesh.nC))
jtv = regularization.JointTotalVariation(mesh,
wire_map=wires,
indActive=actv)
self.mesh = mesh
self.jtv = jtv
self.x0 = np.random.rand(len(mesh) * 2)
def plotVectorSectionsOctree(
mesh,
m,
normal="X",
ind=0,
vmin=None,
vmax=None,
scale=1.0,
vec="k",
axs=None,
actvMap=None,
fill=True,
):
"""
Plot section through a 3D tensor model
"""
# plot recovered model
normalInd = {"X": 0, "Y": 1, "Z": 2}[normal]
antiNormalInd = {"X": [1, 2], "Y": [0, 2], "Z": [0, 1]}[normal]
h2d = (mesh.h[antiNormalInd[0]], mesh.h[antiNormalInd[1]])
x2d = (mesh.x0[antiNormalInd[0]], mesh.x0[antiNormalInd[1]])
#: Size of the sliced dimension
szSliceDim = len(mesh.h[normalInd])
if ind is None:
ind = int(szSliceDim // 2)
cc_tensor = [None, None, None]
for i in range(3):
cc_tensor[i] = np.cumsum(np.r_[mesh.x0[i], mesh.h[i]])
cc_tensor[i] = (cc_tensor[i][1:] + cc_tensor[i][:-1]) * 0.5
slice_loc = cc_tensor[normalInd][ind]
# Create a temporary TreeMesh with the slice through
temp_mesh = TreeMesh(h2d, x2d)
level_diff = mesh.max_level - temp_mesh.max_level
XS = [None, None, None]
XS[antiNormalInd[0]], XS[antiNormalInd[1]] = np.meshgrid(
cc_tensor[antiNormalInd[0]], cc_tensor[antiNormalInd[1]])
XS[normalInd] = np.ones_like(XS[antiNormalInd[0]]) * slice_loc
loc_grid = np.c_[XS[0].reshape(-1), XS[1].reshape(-1), XS[2].reshape(-1)]
inds = np.unique(mesh._get_containing_cell_indexes(loc_grid))
grid2d = mesh.gridCC[inds][:, antiNormalInd]
levels = mesh._cell_levels_by_indexes(inds) - level_diff
temp_mesh.insert_cells(grid2d, levels)
tm_gridboost = np.empty((temp_mesh.nC, 3))
tm_gridboost[:, antiNormalInd] = temp_mesh.gridCC
tm_gridboost[:, normalInd] = slice_loc
# Interpolate values to mesh.gridCC if not 'CC'
mx = actvMap * m[:, 0]
my = actvMap * m[:, 1]
mz = actvMap * m[:, 2]
m = np.c_[mx, my, mz]
# Interpolate values from mesh.gridCC to grid2d
ind_3d_to_2d = mesh._get_containing_cell_indexes(tm_gridboost)
v2d = m[ind_3d_to_2d, :]
amp = np.sum(v2d**2.0, axis=1)**0.5
if axs is None:
axs = plt.subplot(111)
if fill:
temp_mesh.plotImage(amp, ax=axs, clim=[vmin, vmax], grid=True)
axs.quiver(
temp_mesh.gridCC[:, 0],
temp_mesh.gridCC[:, 1],
v2d[:, antiNormalInd[0]],
v2d[:, antiNormalInd[1]],
pivot="mid",
scale_units="inches",
scale=scale,
linewidths=(1, ),
edgecolors=(vec),
headaxislength=0.1,
headwidth=10,
headlength=30,
)
