remanence_model[ind_sphere, :] = effective_susceptibility_sphere
# Define effective susceptibility model as a vector np.r_[chi_x, chi_y, chi_z]
plotting_model = susceptibility_model + remanence_model
model = mkvc(plotting_model)
# Plot Effective Susceptibility Model
fig = plt.figure(figsize=(9, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
plotting_model = np.sqrt(np.sum(plotting_model, axis=1)**2)
ax1 = fig.add_axes([0.1, 0.12, 0.73, 0.78])
mesh.plotSlice(
plotting_map * plotting_model,
normal="Y",
ax=ax1,
ind=int(mesh.hy.size / 2),
grid=True,
clim=(np.min(plotting_model), np.max(plotting_model)),
)
ax1.set_title("MVI Model at y = 0 m")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax2 = fig.add_axes([0.85, 0.12, 0.05, 0.78])
norm = mpl.colors.Normalize(vmin=np.min(plotting_model),
vmax=np.max(plotting_model))
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label("Effective Susceptibility Amplitude (SI)",
rotation=270,
labelpad=15,
size=12)
###############################################################
# Plotting True and Recovered Conductivity Model
# ----------------------------------------------
#
# Plot True Model
fig = plt.figure(figsize=(10, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
ax1 = fig.add_axes([0.15, 0.15, 0.67, 0.75])
mesh.plotSlice(
plotting_map * true_conductivity_model_log10,
ax=ax1,
normal="Y",
ind=int(len(mesh.hy) / 2),
grid=False,
clim=(true_conductivity_model_log10.min(),
true_conductivity_model_log10.max()),
pcolor_opts={"cmap": mpl.cm.viridis},
)
ax1.set_title("True Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax1.set_xlim([-1000, 1000])
ax1.set_ylim([-1000, 0])
ax2 = fig.add_axes([0.84, 0.15, 0.03, 0.75])
norm = mpl.colors.Normalize(vmin=true_conductivity_model_log10.min(),
vmax=true_conductivity_model_log10.max())
cbar = mpl.colorbar.ColorbarBase(ax2,
cmap=mpl.cm.viridis,
#sig[M.gridCC[:,2] > -1000] = 3.3 # água
sig[M.gridCC[:, 2] > 0] = 1e-12 # ar
sigBG = np.zeros(M.nC) + conds[1]
#sigBG[M.gridCC[:, 2] > -1000] = 3.3
sigBG[M.gridCC[:, 2] > 0] = 1e-12
# MESH 1D (para modelo de background)
mesh1d = simpeg.Mesh.TensorMesh([M.hz], np.array([M.x0[2]]))
sigBG1d = np.zeros(mesh1d.nC) + conds[1]
#sigBG1d[mesh1d.gridCC > -1000] = 3.3
sigBG1d[mesh1d.gridCC > 0] = 1e-12
fig, axes = plt.subplots(num=3, clear=True)
M.plotSlice(np.log(sig), grid=True, normal='y', ax=axes)
plt.show()
#------------------------------------------------------------------------------
# Fim modelo e malha -
#------------------------------------------------------------------------------
#------------------------------------------------------------------------------
# Iniciar modelagem -
#------------------------------------------------------------------------------
rx_x = np.array([0.])
rx_y = np.array([0.])
rx_z = np.array([0.])
rx_loc = np.hstack((simpeg.Utils.mkvc(rx_x, 2), simpeg.Utils.mkvc(rx_y, 2),
np.zeros((np.prod(rx_x.shape), 1))))
xyz,
octree_levels=[2, 2],
method='box',
finalize=False)
mesh.finalize()
# The bottom west corner
x0 = mesh.x0
# The total number of cells
nC = mesh.nC
# An (nC, 2) array containing the cell-center locations
cc = mesh.gridCC
# A boolean array specifying which cells lie on the boundary
bInd = mesh.cellBoundaryInd
# Cell volumes
v = mesh.vol
fig = plt.figure(figsize=(6, 6))
ax = fig.add_subplot(111)
mesh.plotSlice(np.log10(v),
normal='Y',
ax=ax,
ind=int(mesh.hy.size / 2),
grid=True)
ax.set_title('Cell Log-Volumes at Y = 0 m')
# You can also use SimPEG utilities to add structures to the model more concisely
ind_sphere = model_builder.getIndicesSphere(np.r_[35.0, 0.0, -40.0], 15.0,
mesh.gridCC)
ind_sphere = ind_sphere[ind_active]
model[ind_sphere] = sphere_density
# Plot Density Contrast Model
fig = plt.figure(figsize=(9, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
ax1 = fig.add_axes([0.1, 0.12, 0.73, 0.78])
mesh.plotSlice(
plotting_map * model,
normal="Y",
ax=ax1,
ind=int(mesh.hy.size / 2),
grid=True,
clim=(np.min(model), np.max(model)),
pcolorOpts={"cmap": "viridis"},
)
ax1.set_title("Model slice at y = 0 m")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax2 = fig.add_axes([0.85, 0.12, 0.05, 0.78])
norm = mpl.colors.Normalize(vmin=np.min(model), vmax=np.max(model))
cbar = mpl.colorbar.ColorbarBase(ax2,
norm=norm,
orientation="vertical",
cmap=mpl.cm.viridis)
cbar.set_label("$g/cm^3$", rotation=270, labelpad=15, size=12)
np.r_[350., 0., -300.], 160., mesh.cell_centers[ind_active, :]
)
conductivity_model[ind_resistor] = resistor_value
# Plot Conductivity Model
fig = plt.figure(figsize=(10, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
log_mod = np.log10(conductivity_model)
ax1 = fig.add_axes([0.15, 0.15, 0.67, 0.75])
mesh.plotSlice(
plotting_map * log_mod,
ax=ax1,
normal="Y",
ind=int(len(mesh.hy) / 2),
grid=True,
clim=(np.log10(resistor_value), np.log10(conductor_value)),
pcolor_opts={"cmap": mpl.cm.viridis},
)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax1.set_xlim([-1000, 1000])
ax1.set_ylim([-1000, 0])
ax2 = fig.add_axes([0.84, 0.15, 0.03, 0.75])
norm = mpl.colors.Normalize(
vmin=np.log10(resistor_value), vmax=np.log10(conductor_value)
)
cbar = mpl.colorbar.ColorbarBase(
ind_resistor = model_builder.getIndicesSphere(np.r_[350., 0., -300.], 160.,
mesh.cell_centers[ind_active, :])
conductivity_model[ind_resistor] = resistor_value
# Plot Conductivity Model
fig = plt.figure(figsize=(10, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
log_mod = np.log10(conductivity_model)
ax1 = fig.add_axes([0.15, 0.15, 0.68, 0.75])
mesh.plotSlice(
plotting_map * log_mod,
ax=ax1,
normal="Y",
ind=int(len(mesh.hy) / 2),
grid=True,
clim=(np.log10(resistor_value), np.log10(conductor_value)),
pcolor_opts={"cmap": mpl.cm.viridis},
)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax1.set_xlim([-1000, 1000])
ax1.set_ylim([-1000, 0])
ax2 = fig.add_axes([0.84, 0.15, 0.03, 0.75])
norm = mpl.colors.Normalize(vmin=np.log10(resistor_value),
vmax=np.log10(conductor_value))
cbar = mpl.colorbar.ColorbarBase(ax2,
cmap=mpl.cm.viridis,
# Load the true model (was defined on the whole mesh) and extract only the
# values on active cells.
true_model = np.loadtxt(str(model_filename))
true_model = np.log(true_model[ind_active])
# Plot True Model
fig = plt.figure(figsize=(9, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
ax1 = fig.add_axes([0.1, 0.1, 0.73, 0.8])
mesh.plotSlice(
plotting_map * true_model,
normal="Y",
ax=ax1,
ind=int(mesh.hy.size / 2),
grid=True,
clim=(np.min(true_model), np.max(true_model)),
pcolorOpts={"cmap": "jet"},
)
ax1.set_title("Model slice at y = 0 m")
ax2 = fig.add_axes([0.85, 0.1, 0.05, 0.8])
norm = mpl.colors.Normalize(vmin=np.min(true_model), vmax=np.max(true_model))
cbar = mpl.colorbar.ColorbarBase(ax2,
norm=norm,
orientation="vertical",
cmap=mpl.cm.jet,
format="%.1f")
cbar.set_label("$S/m$", rotation=270, labelpad=15, size=12)
& (mesh.gridCC[ind_active, 2] > -275.0)
& (mesh.gridCC[ind_active, 2] < -75.0))
model[ind_block] = block_conductivity
# Plot Resistivity Model
mpl.rcParams.update({"font.size": 12})
fig = plt.figure(figsize=(7, 6))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
log_model = np.log10(model)
ax1 = fig.add_axes([0.13, 0.1, 0.6, 0.85])
mesh.plotSlice(
plotting_map * log_model,
normal="Y",
ax=ax1,
ind=int(mesh.hx.size / 2),
grid=True,
clim=(np.log10(background_conductivity), np.log10(block_conductivity)),
)
ax1.set_title("Conductivity Model at Y = 0 m")
ax2 = fig.add_axes([0.75, 0.1, 0.05, 0.85])
norm = mpl.colors.Normalize(vmin=np.log10(background_conductivity),
vmax=np.log10(block_conductivity))
cbar = mpl.colorbar.ColorbarBase(ax2,
norm=norm,
orientation="vertical",
format="$10^{%.1f}$")
cbar.set_label("Conductivity [S/m]", rotation=270, labelpad=15, size=12)
######################################################
& (mesh.gridCC[ind_active, 2] > -600.0)
& (mesh.gridCC[ind_active, 2] < -200.0))
conductivity_model[ind_resistor] = resistor_value
# Plot Conductivity Model
fig = plt.figure(figsize=(11, 4))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
log_mod = np.log10(conductivity_model)
ax1 = fig.add_axes([0.1, 0.12, 0.7, 0.78])
mesh.plotSlice(
plotting_map * log_mod,
ax=ax1,
normal='Y',
ind=int(len(mesh.hy) / 2),
grid=True,
clim=(np.log10(1e-3), np.log10(conductor_value)),
pcolor_opts={"cmap": "viridis"},
)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")
ax1.set_xlim([-2000, 2000])
ax1.set_ylim([-2000, 0])
ax2 = fig.add_axes([0.83, 0.12, 0.03, 0.78])
norm = mpl.colors.Normalize(vmin=np.log10(resistor_value),
vmax=np.log10(conductor_value))
cbar = mpl.colorbar.ColorbarBase(ax2,
norm=norm,
for ii in range(0, 8):
model += (pc[ii] * np.exp(-((xyzc[:, 0] - x_0[ii])**2) / var_x[ii]) *
np.exp(-((xyzc[:, 1] - y_0[ii])**2) / var_y[ii]) *
np.exp(-((xyzc[:, 2] - z_0[ii])**2) / var_z[ii]))
# Plot Model
mpl.rcParams.update({"font.size": 12})
fig = plt.figure(figsize=(7.5, 7))
plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
ax1 = fig.add_axes([0.09, 0.12, 0.72, 0.77])
mesh.plotSlice(
plotting_map * model,
normal="Z",
ax=ax1,
ind=0,
grid=True,
clim=(np.min(model), np.max(model)),
pcolorOpts={"cmap": "magma_r"},
)
ax1.set_title("Model slice at z = 0 m")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("y (m)")
ax2 = fig.add_axes([0.83, 0.12, 0.05, 0.77])
norm = mpl.colors.Normalize(vmin=np.min(model), vmax=np.max(model))
cbar = mpl.colorbar.ColorbarBase(ax2,
norm=norm,
orientation="vertical",
cmap=mpl.cm.magma_r)
cbar.set_label("Amalgamated Magnetic Property (SI)",