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examples/realcase1_regional_tomography_California/.DS_Store vendored Normal file
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version: 3
#################################################
# computational domian #
#################################################
domain:
min_max_dep: [-5, 45] # depth in km
min_max_lat: [-2.0, 2.4] # latitude in degree
min_max_lon: [-0.8, 0.8] # longitude in degree
n_rtp: [51, 89, 33] # number of nodes in depth,latitude,longitude direction
#################################################
# traveltime data file path #
#################################################
source:
src_rec_file: 1_src_rec_files/src_rec_file.dat # source receiver file path
swap_src_rec: true # swap source and receiver
#################################################
# initial model file path #
#################################################
model:
init_model_path: 2_models/model_init_N51_89_33.h5 # path to initial model file
#################################################
# parallel computation settings #
#################################################
parallel: # parameters for parallel computation
n_sims: 8 # number of simultanoues runs (parallel the sources)
ndiv_rtp: [1, 1, 1] # number of subdivision on each direction (parallel the computional domain)
############################################
# output file setting #
############################################
output_setting:
output_dir: OUTPUT_FILES/OUTPUT_FILES_inv # path to output director (default is ./OUTPUT_FILES/)
output_source_field: false # True: output the traveltime field and adjoint field of all sources at each iteration. Default: false. File: 'out_data_sim_group_X'.
output_kernel: true
output_final_model: true # True: output merged final model. This file can be used as the input model for TomoATT. Default: true. File: 'model_final.h5'.
output_middle_model: true # True: output merged intermediate models during inversion. This file can be used as the input model for TomoATT. Default: false. File: 'middle_model_step_XXXX.h5'
output_in_process: true # True: output at each inv iteration, otherwise, only output step 0, Niter-1, Niter. Default: true. File: 'out_data_sim_group_0'.
output_in_process_data: true # True: output src_rec_file at each inv iteration, otherwise, only output step 0, Niter-2, Niter-1. Default: true. File: 'src_rec_file_step_XXXX.dat'
single_precision_output: false # True: output results in single precision. Default: false.
verbose_output_level: 0 # output internal parameters, (to do)
output_file_format: 0 # 0: hdf5, 1: ascii
# output files:
# File: 'out_data_grid.h5'. Keys: ['Mesh']['elem_conn'], element index;
# ['Mesh']['node_coords_p'], phi coordinates of nodes;
# ['Mesh']['node_coords_t'], theta coordinates of nodes;
# ['Mesh']['node_coords_r'], r coordinates of nodes;
# ['Mesh']['node_coords_x'], phi coordinates of elements;
# ['Mesh']['node_coords_y'], theta coordinates of elements;
# ['Mesh']['node_coords_z'], r coordinates of elements;
# File: 'out_data_sim_group_0'. Keys: ['model']['vel_inv_XXXX'], velocity model at iteration XXXX;
# ['model']['xi_inv_XXXX'], xi model at iteration XXXX;
# ['model']['eta_inv_XXXX'], eta model at iteration XXXX
# ['model']['Ks_inv_XXXX'], sensitivity kernel related to slowness at iteration XXXX
# ['model']['Kxi_inv_XXXX'], sensitivity kernel related to xi at iteration XXXX
# ['model']['Keta_inv_XXXX'], sensitivity kernel related to eta at iteration XXXX
# ['model']['Ks_density_inv_XXXX'], kernel density of Ks at iteration XXXX
# ['model']['Kxi_density_inv_XXXX'], kernel density of Kxi at iteration XXXX
# ['model']['Keta_density_inv_XXXX'], kernel density of Keta at iteration XXXX
# ['model']['Ks_over_Kden_inv_XXXX'], slowness kernel over kernel density at iteration XXXX
# ['model']['Kxi_over_Kden_inv_XXXX'], xi kernel over kernel density at iteration XXXX
# ['model']['Keta_over_Kden_inv_XXXX'], eta kernel over kernel density at iteration XXXX
# ['model']['Ks_update_inv_XXXX'], slowness kernel over kernel density at iteration XXXX, smoothed by inversion grid
# ['model']['Kxi_update_inv_XXXX'], xi kernel over kernel density at iteration XXXX, smoothed by inversion grid
# ['model']['Keta_update_inv_XXXX'], eta kernel over kernel density at iteration XXXX, smoothed by inversion grid
# ['1dinv']['vel_1dinv_inv_XXXX'], 2d velocity model at iteration XXXX, in 1d inversion mode
# ['1dinv']['r_1dinv'], r coordinates (depth), in 1d inversion mode
# ['1dinv']['t_1dinv'], t coordinates (epicenter distance), in 1d inversion mode
# File: 'src_rec_file_step_XXXX.dat' or 'src_rec_file_forward.dat'. The synthetic traveltime data file.
# File: 'final_model.h5'. Keys: ['eta'], ['xi'], ['vel'], the final model.
# File: 'middle_model_step_XXXX.h5'. Keys: ['eta'], ['xi'], ['vel'], the model at step XXXX.
# File: 'inversion_grid.txt'. The location of inversion grid nodes
# File: 'objective_function.txt'. The objective function value at each iteration
# File: 'out_data_sim_group_X'. Keys: ['src_YYYY']['time_field_inv_XXXX'], traveltime field of source YYYY at iteration XXXX;
# ['src_YYYY']['adjoint_field_inv_XXXX'], adjoint field of source YYYY at iteration XXXX;
# ['1dinv']['time_field_1dinv_YYYY_inv_XXXX'], 2d traveltime field of source YYYY at iteration XXXX, in 1d inversion mode
# ['1dinv']['adjoint_field_1dinv_YYYY_inv_XXXX'], 2d adjoint field of source YYYY at iteration XXXX, in 1d inversion mode
#################################################
# inversion or forward modeling #
#################################################
# run mode
# 0 for forward simulation only,
# 1 for inversion
# 2 for earthquake relocation
# 3 for inversion + earthquake relocation
# 4 for 1d model inversion
run_mode: 1
###################################################
# model update parameters setting #
###################################################
model_update:
max_iterations: 80 # maximum number of inversion iterations
step_length: 0.01 # the initial step length of model perturbation. 0.01 means maximum 1% perturbation for each iteration.
# parameters for optim_method 0 (gradient_descent)
optim_method_0:
# if step_method:1. if the angle between the current and the previous gradients is greater than step_length_gradient_angle, step size -> step length * step_length_change[0].
# otherwise, step size -> step length * step_length_change[1].
step_length_gradient_angle: 120 # default: 120.0
step_length_change: [0.5, 1.41] # default: [0.5,1.2]
Kdensity_coe: 0.3 # default: 0.0, range: 0.0 - 1.0
# parameters for smooth method 0 (multigrid model parametrization)
# inversion grid can be viewed in OUTPUT_FILES/inversion_grid.txt
n_inversion_grid: 5 # number of inversion grid sets
uniform_inv_grid_dep: false # true if use uniform inversion grid for dep, false if use flexible inversion grid
uniform_inv_grid_lat: false # true if use uniform inversion grid for lat, false if use flexible inversion grid
uniform_inv_grid_lon: false # true if use uniform inversion grid for lon, false if use flexible inversion grid
# settings for uniform inversion grid
n_inv_dep_lat_lon: [3, 11, 11] # number of inversion grid in depth, latitude, and longitude direction
min_max_dep_inv: [-5 , 5] # inversion grid for vel in depth (km)
min_max_lat_inv: [0, 1] # inversion grid for vel in latitude (degree)
min_max_lon_inv: [0, 1] # inversion grid for vel in longitude (degree)
# settings for flexible inversion grid
dep_inv: [-5, -2, 0, 3, 7, 12, 17, 23, 30, 38, 47, 57] # inversion grid for vel in depth (km)
lat_inv: [-2.5, -2.2, -1.9, -1.6, -1.3, -1.0, -0.7, -0.4, -0.1, 0.2, 0.5, 0.8, 1.1, 1.4, 1.7, 2.0, 2.3, 2.6] # inversion grid for vel in latitude (degree)
lon_inv: [-1.2, -0.9, -0.6, -0.3, 0, 0.3, 0.6, 0.9, 1.2] # inversion grid for vel in longitude (degree)
trapezoid: [1, 0, 50] # usually set as [1.0, 0.0, 50.0] (default)
# if we want to use another inversion grid for inverting anisotropy, set invgrid_ani: true (default: false)
invgrid_ani: true
# ---------- flexible inversion grid setting for anisotropy ----------
# settings for flexible inversion grid for anisotropy
dep_inv_ani: [-5, -2, 0, 3, 7, 12, 17, 23, 30, 38, 47, 57] # inversion grid for ani in depth (km)
lat_inv_ani: [-2.8, -2.3, -1.8, -1.3, -0.8, -0.3, 0.2, 0.7, 1.2, 1.7, 2.2, 2.7] # inversion grid for ani in latitude (degree)
lon_inv_ani: [-1.2, -0.9, -0.6, -0.3, 0, 0.3, 0.6, 0.9, 1.2] # inversion grid for ani in longitude (degree)
trapezoid_ani: [1, 0, 50] # usually set as [1.0, 0.0, 50.0] (default)
# Carefully change trapezoid and trapezoid_ani, if you really want to use trapezoid inversion grid, increasing the inversion grid spacing with depth to account for the worse data coverage in greater depths.
# The trapezoid_ inversion grid with index (i,j,k) in longitude, latitude, and depth is defined as:
# if dep_inv[k] < trapezoid[1], lon = lon_inv[i];
# lat = lat_inv[j];
# dep = dep_inv[k];
# if trapezoid[1] <= dep_inv[k] < trapezoid[2], lon = mid_lon_inv+(lon_inv[i]-mid_lon_inv)*(dep_inv[k]-trapezoid[1])/(trapezoid[2]-trapezoid[1])*trapezoid[0];
# lat = mid_lat_inv+(lat_inv[i]-mid_lat_inv)*(dep_inv[k]-trapezoid[1])/(trapezoid[2]-trapezoid[1])*trapezoid[0];
# dep = dep_inv[k];
# if trapezoid[2] <= dep_inv[k], lon = mid_lon_inv+(lon_inv[i]-mid_lon_inv)*trapezoid[0];
# lat = mid_lat_inv+(lat_inv[i]-mid_lat_inv)*trapezoid[0];
# dep = dep_inv[k];
# The shape of trapezoid inversion gird (x) looks like:
#
# lon_inv[0] [1] [2] [3] [4]
# |<-------- (lon_inv[end] - lon_inv[0]) ---->|
# dep_inv[0] | x x x x x |
# | |
# dep_inv[1] | x x x x x |
# | |
# dep_inv[2] = trapezoid[1] / x x x x x \
# / \
# dep_inv[3] / x x x x x \
# / \
# dep_inv[4] = trapezoid[2] / x x x x x \
# | |
# dep_inv[5] | x x x x x |
# | |
# dep_inv[6] | x x x x x |
# |<---- trapezoid[0]* (lon_inv[end] - lon_inv[0]) ------>|
# -------------- using absolute traveltime data --------------
abs_time:
use_abs_time: true # 'true' for using absolute traveltime data to update model parameters; 'false' for not using (no need to set parameters in this section)
# -------------- using common source differential traveltime data --------------
cs_dif_time:
use_cs_time: false # 'true' for using common source differential traveltime data to update model parameters; 'false' for not using (no need to set parameters in this section)
# -------------- using common receiver differential traveltime data --------------
cr_dif_time:
use_cr_time: false # 'true' for using common receiver differential traveltime data to update model parameters; 'false' for not using (no need to set parameters in this section)
# -------------- inversion parameters --------------
update_slowness : true # update slowness (velocity) or not. default: true
update_azi_ani : true # update azimuthal anisotropy (xi, eta) or not. default: false

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examples/realcase1_regional_tomography_California/README.md Normal file
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# Real case of regional tomography in central California near Parkfield
This is a real case to invert traveltimes for velocity heterogeneity and azimuthal anisotropy in central California near Parkfield
Reference:
[1] J. Chen, G. Chen, M. Nagaso, and P. Tong, Adjoint-state traveltime tomography for azimuthally anisotropic media in spherical coordinates. Geophys. J. Int., 234 (2023), pp. 712-736.
https://doi.org/10.1093/gji/ggad093
[2] J. Chen, M. Nagaso, M. Xu, and P. Tong, TomoATT: An open-source package for Eikonal equation-based adjoint-state traveltime tomography for seismic velocity and azimuthal anisotropy, submitted.
https://doi.org/10.48550/arXiv.2412.00031
Python modules are required to initiate the inversion and to plot final results:
- h5py
- PyTomoAT
- Pygmt
- gmt
Run this example:
1. Run bash script `bash run_this_example.sh` to execute the test.
2. After inversion, run `plot_output.py` to plot the results.
The imaging results:
![](img/imaging_result.jpg)

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examples/realcase1_regional_tomography_California/plot_output.py Normal file
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# %%
import pygmt
pygmt.config(FONT="16p", IO_SEGMENT_MARKER="<<<")
import os
# %%
from pytomoatt.model import ATTModel
from pytomoatt.data import ATTData
import numpy as np
# %%
# read model files
Ngrid = [51,89,33]
data_file = '2_models/model_init_N%d_%d_%d.h5'%(Ngrid[0],Ngrid[1],Ngrid[2])
par_file = '3_input_params/input_params_real.yaml'
model = ATTModel.read(data_file, par_file)
initial_model = model.to_xarray()
data_file = 'OUTPUT_FILES/OUTPUT_FILES_real/final_model.h5'
model = ATTModel.read(data_file, par_file)
inv_model = model.to_xarray()
# %%
# read earthquakes and stations
from pytomoatt.src_rec import SrcRec
# read src_rec_file
sr = SrcRec.read("1_src_rec_files/src_rec_file.dat")
# rotate back to original coordinates
central_lat = 35.6
central_lon = -120.45
rotation_angle = -30
sr.rotate(central_lat, central_lon, rotation_angle, reverse=True)
# get the coordinates of the stations and earthquakes
stations = sr.receivers[['stlo','stla','stel']].values.T
earthquakes = sr.sources[['evlo','evla','evdp']].values.T
print(stations.shape)
print(earthquakes.shape)
# %%
# study region
import sys
sys.path.append('../utils')
import functions_for_data as ffd
lat1 = -1.8; lat2 = 2.2;
lon1 = -0.7; lon2 = 0.7;
lat_lon_rotate = np.array([[lon1,lat1],[lon1,lat2],[lon2,lat2],[lon2,lat1],[lon1,lat1]])
lat_lon = ffd.rtp_rotation_reverse(lat_lon_rotate[:,1],lat_lon_rotate[:,0],central_lat,central_lon,rotation_angle)
studt_lat = lat_lon[0]
studt_lon = lat_lon[1]
# %%
# load topography
region = [-122.8,-118.5,33.5,38]
grid_topo = pygmt.datasets.load_earth_relief(resolution="01m", region=region)
grid_gra = pygmt.grdgradient(grid = grid_topo, azimuth = 0)
# %%
def line_read(file):
doc=open(file,'r')
file = doc.readlines()
doc.close()
lat = []; lon = [];
for info in file:
tmp = info.split()
lon.append(float(tmp[0]))
lat.append(float(tmp[1]))
return((lat,lon))
# %%
# plot imgaing results
fig = pygmt.Figure()
try:
os.mkdir("img")
except:
pass
# ------------------ Sub fig 1. topography ------------------
region = [-122.8,-118.5,33.5,38]
frame = ["xa1","ya1","nSWe"]
projection = "M10c"
# topography
pygmt.makecpt(cmap="globe", series=[-4000,4000], background = True)
fig.grdimage(grid=grid_topo, shading = grid_gra, projection=projection, frame=frame,region=region)
# study region
fig.plot(x = studt_lon, y = studt_lat, pen = "1.5p,red")
# earthquakes
fig.plot(x = earthquakes[0,:], y = earthquakes[1,:], style = "c0.02c", fill = "red",label = "Earthquake")
# stations
fig.plot(x = stations[0,:], y = stations[1,:], style = "t0.2c", fill = "blue", pen = "white", label = "Station")
fig.basemap(region=[0,1,0,1], frame=["wesn+gwhite"], projection="X4c/2c")
fig.plot(x=0.1, y=0.3, style='c0.2c', fill='red')
fig.text(text="Earthquake", x=0.2, y=0.3, font="16p,Helvetica", justify="LM")
fig.plot(x=0.1, y=0.7, style='t0.4c', fill='blue', pen='black')
fig.text(text="Station", x=0.2, y=0.7, font="16p,Helvetica", justify="LM")
# ------------------ Sub fig 2. colorbar ------------------
fig.shift_origin(xshift= 2, yshift= -2)
pygmt.makecpt(cmap="globe", series=[-4000,4000], background = True)
fig.colorbar(frame = ["a%f"%(4000),"y+lElevation (m)"], position="+e+w4c/0.3c+h")
fig.shift_origin(yshift=-2)
pygmt.makecpt(cmap="../utils/svel13_chen.cpt", series=[-8, 8], background=True, reverse=False)
fig.colorbar(frame = ["a%f"%(4),"y+ldlnVp (%)"], position="+e+w4c/0.3c+h")
fig.shift_origin(yshift=-2)
pygmt.makecpt(cmap="cool", series=[0, 0.08], background=True, reverse=False)
fig.colorbar(frame = ["a%f"%(0.04),"y+lAnisotropy"], position="+ef+w4c/0.3c+h")
# ------------------ Sub fig 3. model ------------------
fig.shift_origin(xshift = 10, yshift=8)
region_oblique = [-0.7,0.7,-2.2,1.8]
projection = "OA%s/%s/%s/4c"%(central_lon,central_lat,rotation_angle-90.0)
perspective = "30/90"
spacing = "1m"
depth_list = [4,8,16]
for idepth, depth in enumerate(depth_list):
# initial model
vel_init = initial_model.interp_dep(depth, field='vel')
# output model
vel_inv = inv_model.interp_dep(depth, field='vel') # velocity
epsilon_inv = inv_model.interp_dep(depth, field='epsilon') # magnitude of anisotropy
# fast velocity directions
samp_interval = 3
ani_thd = 0.015
length = 20
width = 0.1
ani_inv_phi = inv_model.interp_dep(depth, field='phi', samp_interval=samp_interval)
ani_inv_epsilon = inv_model.interp_dep(depth, field='epsilon', samp_interval=samp_interval)
ani_inv = np.hstack([ani_inv_phi, ani_inv_epsilon[:,2].reshape(-1, 1)*length, np.ones((ani_inv_epsilon.shape[0],1))*width]) # lon, lat, angle, length, width
idx = np.where(ani_inv_epsilon[:,2] > ani_thd)
ani = ani_inv[idx[0],:]
# --------- plot velocity ------------
if idepth == 0:
frame = ["xa100","ya1","nSwE"]
elif idepth == len(depth_list)-1:
frame = ["xa100","ya1","NsWe"]
else:
frame = ["xa100","ya1","nswe"]
fig.basemap(region=region_oblique, frame=frame, projection=projection, perspective=perspective)
pygmt.makecpt(cmap="../utils/svel13_chen.cpt", series=[-8, 8], background=True, reverse=False)
x = vel_init[:,0]; y = vel_init[:,1]; value = (vel_inv[:,2] - vel_init[:,2])/vel_init[:,2] * 100
y,x = ffd.rtp_rotation_reverse(y,x,central_lat,central_lon,rotation_angle)
grid = pygmt.surface(x=x, y=y, z=value, spacing=spacing,region=region)
fig.grdimage(frame=frame,grid = grid,projection=projection, region=region_oblique,perspective=perspective) # nan_transparent may work
# tectonic setting
fig.coast(region=region_oblique, frame=frame, projection=projection, perspective=perspective, shorelines="1p,black") # coastlines
(SAFy,SAFx) = line_read("tectonics/SAF")
fig.plot(x = SAFx, y = SAFy, pen = '3.0p,black', perspective = perspective) # SAF
if idepth == 0:
fig.text(text = "SMB", x = -120.45 , y = 35.0, font = "16p,Helvetica-Bold,black", angle = 150, fill = "lightblue", perspective = perspective) # SMB
fig.text(text = "FT", x = -120.6 , y = 36.50, font = "16p,Helvetica-Bold,black", angle = 150, fill = "lightblue", perspective = perspective) # Franciscan terrane
fig.text(text = "ST", x = -121.1 , y = 36.0, font = "16p,Helvetica-Bold,black", angle = 150, fill = "lightblue", perspective = perspective) # Salinian terrane
fig.text(text = "TR", x = -119.30 , y = 34.70, font = "16p,Helvetica-Bold,black", angle = 150, fill = "lightblue", perspective = perspective) # Coast Ranges
# depth label
fig.text(text="%d km"%(depth), x = -119.8 , y = 34.0, font = "16p,Helvetica-Bold,black", angle = 180, fill = "white", perspective = perspective) # Coast Ranges
# --------- plot anisotropy ------------
fig.shift_origin(yshift=-12)
fig.basemap(region=region_oblique, frame=frame, projection=projection, perspective=perspective)
pygmt.makecpt(cmap="cool", series=[0, 0.08], background=True)
value = epsilon_inv[:,2]
grid = pygmt.surface(x=x, y=y, z=value, spacing=spacing,region=region)
fig.grdimage(frame=frame,grid = grid,projection=projection, region=region_oblique,perspective=perspective) # nan_transparent may work
# tectonic setting
fig.coast(region=region_oblique, frame=frame, projection=projection, perspective=perspective, shorelines="1p,black") # coastlines
(line_y,line_x) = line_read("tectonics/SAF_creeping")
fig.plot(x = line_x, y = line_y, pen = '3.0p,black',perspective = perspective)
(line_y,line_x) = line_read("tectonics/SAF_transition")
fig.plot(x = line_x, y = line_y, pen = '3.0p,red',perspective = perspective)
(line_y,line_x) = line_read("tectonics/SAF_locked")
fig.plot(x = line_x, y = line_y, pen = '3.0p,blue',perspective = perspective)
# anisotropy
if len(ani) > 0:
# rotate back to original coordinates
x = ani[:,0]; y = ani[:,1]
y,x = ffd.rtp_rotation_reverse(y,x,central_lat,central_lon,rotation_angle)
ani[:,0] = x; ani[:,1] = y; # no need to modify the angle, because the porjection angle and rotate angle are the same
fig.plot(ani, style='j', fill='yellow1', pen='0.5p,black',perspective=perspective)
fig.shift_origin(xshift=6,yshift=12)
fig.show()
fig.savefig("img/imaging_result.png")

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examples/realcase1_regional_tomography_California/prepare_input_files.py Normal file
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# %%
# download src_ref_files from Zenodo
import os
import requests
url = 'https://zenodo.org/records/14065341/files/src_rec_file.dat?download=1'
path = "1_src_rec_files/src_rec_file.dat"
# check file existence
if not os.path.exists(path):
try:
os.mkdir("1_src_rec_files")
except:
pass
print("Downloading src_rec_file.dat from Zenodo...")
response = requests.get(url, stream=True)
with open(path, 'wb') as out_file:
out_file.write(response.content)
print("Download complete.")
else:
print("src_rec_file.dat already exists.")
# %%
# download initial model from Zenodo
url = 'https://zenodo.org/records/14065341/files/model_init_N51_89_33.h5?download=1'
path = "2_models/model_init_N51_89_33.h5"
# check file existence
if not os.path.exists(path):
try:
os.mkdir("2_models")
except:
pass
print("Downloading model_init_N51_89_33.h5 from Zenodo...")
response = requests.get(url, stream=True)
with open(path, 'wb') as out_file:
out_file.write(response.content)
print("Download complete.")
else:
print("model_init_N51_89_33.h5 already exists.")

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examples/realcase1_regional_tomography_California/run_this_example.sh Normal file
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#!/bin/bash
# Step 1: Generate necessary input files
python prepare_input_files.py
# Step 2: Run inversion
# # for WSL
# mpirun -n 8 --allow-run-as-root --oversubscribe ../../build/bin/TOMOATT -i 3_input_params/input_params_real.yaml
# for Linux
# mpirun -n 8 ../../build/bin/TOMOATT -i 3_input_params/input_params_real.yaml
# for conda install
mpirun -n 8 TOMOATT -i 3_input_params/input_params_real.yaml
# Step 3 (Optional): Plot the results
python plot_output.py

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examples/realcase1_regional_tomography_California/tectonics/SAF Normal file
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-122.73566 37.96894
-122.70941 37.93895
-122.65033 37.88999
-122.62177 37.83209
-122.59009 37.79618
-122.56673 37.74661
-122.51982 37.71281
-122.47924 37.65959
-122.40956 37.58436
-122.38051 37.54962
-122.32748 37.48461
-122.23632 37.38344
-122.18852 37.34638
-122.15621 37.31470
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10
examples/realcase1_regional_tomography_California/tectonics/SAF_creeping Normal file
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examples/realcase1_regional_tomography_California/tectonics/SAF_locked Normal file
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5
examples/realcase1_regional_tomography_California/tectonics/SAF_transition Normal file
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