Пример #1
0
ind_conductor = ind_conductor[ind_active]
conductivity_model[ind_conductor] = conductor_conductivity

ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -100.0], 60.0, mesh.gridCC)
ind_resistor = ind_resistor[ind_active]
conductivity_model[ind_resistor] = resistor_conductivity

# Plot Conductivity Model
fig = plt.figure(figsize=(9, 4))

plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
norm = LogNorm(vmin=1e-3, vmax=1e-1)

ax1 = fig.add_axes([0.14, 0.17, 0.68, 0.7])
mesh.plot_image(
    plotting_map * conductivity_model, ax=ax1, grid=False, pcolor_opts={"norm": norm}
)
ax1.set_xlim(-600, 600)
ax1.set_ylim(-600, 0)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.84, 0.17, 0.03, 0.7])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label(r"$\sigma$ (S/m)", rotation=270, labelpad=15, size=12)

plt.show()


###############################################################
Пример #2
0
ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -180.0], 60.0,
                                              mesh.gridCC)
true_conductivity_model[ind_resistor] = true_resistor_conductivity

true_conductivity_model[~ind_active] = np.NaN

# Plot True Model
norm = LogNorm(vmin=1e-3, vmax=1e-1)

fig = plt.figure(figsize=(9, 4))
ax1 = fig.add_axes([0.1, 0.12, 0.72, 0.8])
im = mesh.plot_image(
    true_conductivity_model,
    ax=ax1,
    grid=False,
    range_x=[-700, 700],
    range_y=[-700, 0],
    pcolor_opts={"norm": norm},
)
ax1.set_title("True Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.83, 0.12, 0.05, 0.8])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label("$S/m$", rotation=270, labelpad=15, size=12)

plt.show()

# # Plot Recovered Model
fig = plt.figure(figsize=(9, 4))
Пример #3
0
conductivity_model[ind_conductor] = conductor_conductivity

ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -100.0], 60.0,
                                              mesh.gridCC)
ind_resistor = ind_resistor[ind_active]
conductivity_model[ind_resistor] = resistor_conductivity

# Plot Conductivity Model
fig = plt.figure(figsize=(9, 4))

plotting_map = maps.InjectActiveCells(mesh, ind_active, np.nan)
norm = LogNorm(vmin=1e-3, vmax=1e-1)

ax1 = fig.add_axes([0.14, 0.17, 0.68, 0.7])
mesh.plot_image(plotting_map * conductivity_model,
                ax=ax1,
                grid=False,
                pcolor_opts={"norm": norm})
ax1.set_xlim(-600, 600)
ax1.set_ylim(-600, 0)
ax1.set_title("Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.84, 0.17, 0.03, 0.7])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label(r"$\sigma$ (S/m)", rotation=270, labelpad=15, size=12)

plt.show()

###############################################################
# Project Survey to Discretized Topography
Пример #4
0
ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -180.0], 60.0,
                                              mesh.gridCC)
true_conductivity_model[ind_resistor] = true_resistor_conductivity

true_conductivity_model[~ind_active] = np.NaN

# Plot True Model
norm = LogNorm(vmin=1e-3, vmax=1e-1)

fig = plt.figure(figsize=(9, 4))
ax1 = fig.add_axes([0.1, 0.12, 0.72, 0.8])
im = mesh.plot_image(
    true_conductivity_model,
    ax=ax1,
    grid=False,
    range_x=[-700, 700],
    range_y=[-700, 0],
    pcolor_opts={"norm": norm},
)
ax1.set_title("True Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.83, 0.12, 0.05, 0.8])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label("$S/m$", rotation=270, labelpad=15, size=12)

plt.show()

# # Plot Recovered Model
fig = plt.figure(figsize=(9, 4))
Пример #5
0
ind_conductor = model_builder.getIndicesSphere(np.r_[-120.0, -180.0], 60.0, mesh.gridCC)
true_conductivity_model[ind_conductor] = true_conductor_conductivity

ind_resistor = model_builder.getIndicesSphere(np.r_[120.0, -180.0], 60.0, mesh.gridCC)
true_conductivity_model[ind_resistor] = true_resistor_conductivity

true_conductivity_model[~ind_active] = np.NaN

# Plot True Model
norm = LogNorm(vmin=1e-3, vmax=1e-1)

fig = plt.figure(figsize=(9, 4))
ax1 = fig.add_axes([0.14, 0.17, 0.68, 0.7])
im = mesh.plot_image(
    true_conductivity_model, ax=ax1, grid=False, pcolor_opts={"norm": norm}
)
ax1.set_xlim(-600, 600)
ax1.set_ylim(-600, 0)
ax1.set_title("True Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.84, 0.17, 0.03, 0.7])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label("$S/m$", rotation=270, labelpad=15, size=12)

plt.show()

# Plot Recovered Model
fig = plt.figure(figsize=(9, 4))
Пример #6
0
true_conductivity_model[ind_resistor] = true_resistor_conductivity

true_conductivity_model[~ind_active] = np.NaN

############################################################
# Plotting True and Recovered Conductivity Model
# ----------------------------------------------
#

# Plot True Model
norm = LogNorm(vmin=1e-3, vmax=1e-1)

fig = plt.figure(figsize=(9, 4))
ax1 = fig.add_axes([0.14, 0.17, 0.68, 0.7])
im = mesh.plot_image(true_conductivity_model,
                     ax=ax1,
                     grid=False,
                     pcolor_opts={"norm": norm})
ax1.set_xlim(-600, 600)
ax1.set_ylim(-600, 0)
ax1.set_title("True Conductivity Model")
ax1.set_xlabel("x (m)")
ax1.set_ylabel("z (m)")

ax2 = fig.add_axes([0.84, 0.17, 0.03, 0.7])
cbar = mpl.colorbar.ColorbarBase(ax2, norm=norm, orientation="vertical")
cbar.set_label(r"$\sigma$ (S/m)", rotation=270, labelpad=15, size=12)

plt.show()

# # Plot Recovered Model
fig = plt.figure(figsize=(9, 4))
Пример #7
0
    "Smooth Recovered Model",
    "Sparse Recovered Model",
]
plotting_model = [
    true_conductivity_model,
    l2_conductivity,
    recovered_conductivity,
]

for ii in range(0, 3):

    ax1[ii] = fig.add_axes([0.14, 0.75 - 0.3 * ii, 0.68, 0.2])
    mesh.plot_image(
        plotting_model[ii],
        ax=ax1[ii],
        grid=False,
        range_x=[-700, 700],
        range_y=[-600, 0],
        pcolor_opts={"norm": norm},
    )
    ax1[ii].set_xlim(-600, 600)
    ax1[ii].set_ylim(-600, 0)
    ax1[ii].set_title(title_str[ii])
    ax1[ii].set_xlabel("x (m)")
    ax1[ii].set_ylabel("z (m)")

    ax2[ii] = fig.add_axes([0.84, 0.75 - 0.3 * ii, 0.03, 0.2])
    cbar = mpl.colorbar.ColorbarBase(ax2[ii], norm=norm, orientation="vertical")
    cbar.set_label(r"$\sigma$ (S/m)", rotation=270, labelpad=15, size=12)

plt.show()