Result visualization

This part plot the output files for result visualization. Users can directly run the following codes to plot the results automatically.


python plot_output.py

Figures are output as

img/1d_model_inversion.png for the initial model (init), checkerboard model (ckb), and output model (inv).

Here we demonstrate the plotting script step-by-step

1. Load necessary Python modules


import h5py
import matplotlib.pyplot as plt
import numpy as np
import os

2. Read models

We read initial model, the checkerboard model, and the output model as 3D numpy arrays.


dep = np.linspace(50,-10, 61)    
 
with h5py.File("OUTPUT_FILES/OUTPUT_FILES_1dinv_inv/final_model.h5", "r") as f:
    vel_final= np.array(f["vel"])
with h5py.File("2_models/model_init_N61_61_61.h5", "r") as f:
    vel_init = np.array(f["vel"])
with h5py.File("2_models/model_ckb_N61_61_61.h5", "r") as f:
    vel_ckb = np.array(f["vel"])

3. Plot 1D models

Because the three models are horizontally homogeneous, we extract the first colume of the 3D model array, and plot the velocity with respect to depth.


fig = plt.figure(figsize=(6, 6))
ax = fig.add_subplot(111)
ax.plot(vel_init[:,0,0] , dep, label="init")
ax.plot(vel_ckb[:,0,0], dep, label="ckb")
ax.plot(vel_final[:,0,0], dep, label="inv")
ax.grid()
ax.set_xlabel("Velocity (m/s)",fontsize=16)
ax.set_ylabel("Depth (km)",fontsize=16)
ax.get_xaxis().set_tick_params(labelsize=16)
ax.get_yaxis().set_tick_params(labelsize=16)
ax.set_xlim([4.5,8.5])
ax.set_ylim([0,50])
 
plt.gca().invert_yaxis()
plt.legend(fontsize=16)
 
plt.show()
fig.savefig("img/1d_model_inversion.png", dpi=300, bbox_inches="tight", edgecolor="w", facecolor="w")