initial upload
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version: 3
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#################################################
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# computational domian #
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#################################################
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domain:
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min_max_dep: [-10, 50] # depth in km
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min_max_lat: [0, 2] # latitude in degree
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min_max_lon: [0, 2] # longitude in degree
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n_rtp: [61, 61, 61] # number of nodes in depth,latitude,longitude direction
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#################################################
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# traveltime data file path #
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#################################################
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source:
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src_rec_file: OUTPUT_FILES/OUTPUT_FILES_signal/src_rec_file_forward_errloc.dat # source receiver file path
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swap_src_rec: true # swap source and receiver
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#################################################
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# initial model file path #
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#################################################
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model:
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init_model_path: 2_models/model_ckb_N61_61_61.h5 # path to initial model file
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#################################################
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# parallel computation settings #
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#################################################
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parallel: # parameters for parallel computation
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n_sims: 8 # number of simultanoues runs (parallel the sources)
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ndiv_rtp: [1, 1, 1] # number of subdivision on each direction (parallel the computional domain)
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############################################
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# output file setting #
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############################################
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output_setting:
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output_dir: OUTPUT_FILES/OUTPUT_FILES_loc # path to output director (default is ./OUTPUT_FILES/)
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output_final_model: true # output merged final model (final_model.h5) or not.
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output_in_process: false # output model at each inv iteration or not.
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output_in_process_data: false # output src_rec_file at each inv iteration or not.
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output_file_format: 0
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# output files:
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# File: 'out_data_grid.h5'. Keys: ['Mesh']['elem_conn'], element index;
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# ['Mesh']['node_coords_p'], phi coordinates of nodes;
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# ['Mesh']['node_coords_t'], theta coordinates of nodes;
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# ['Mesh']['node_coords_r'], r coordinates of nodes;
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# ['Mesh']['node_coords_x'], phi coordinates of elements;
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# ['Mesh']['node_coords_y'], theta coordinates of elements;
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# ['Mesh']['node_coords_z'], r coordinates of elements;
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# File: 'out_data_sim_group_0'. Keys: ['model']['vel_inv_XXXX'], velocity model at iteration XXXX;
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# ['model']['xi_inv_XXXX'], xi model at iteration XXXX;
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# ['model']['eta_inv_XXXX'], eta model at iteration XXXX
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# ['model']['Ks_inv_XXXX'], sensitivity kernel related to slowness at iteration XXXX
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# ['model']['Kxi_inv_XXXX'], sensitivity kernel related to xi at iteration XXXX
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# ['model']['Keta_inv_XXXX'], sensitivity kernel related to eta at iteration XXXX
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# ['model']['Ks_density_inv_XXXX'], kernel density of Ks at iteration XXXX
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# ['model']['Kxi_density_inv_XXXX'], kernel density of Kxi at iteration XXXX
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# ['model']['Keta_density_inv_XXXX'], kernel density of Keta at iteration XXXX
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# ['model']['Ks_over_Kden_inv_XXXX'], slowness kernel over kernel density at iteration XXXX
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# ['model']['Kxi_over_Kden_inv_XXXX'], xi kernel over kernel density at iteration XXXX
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# ['model']['Keta_over_Kden_inv_XXXX'], eta kernel over kernel density at iteration XXXX
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# ['model']['Ks_update_inv_XXXX'], slowness kernel over kernel density at iteration XXXX, smoothed by inversion grid
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# ['model']['Kxi_update_inv_XXXX'], xi kernel over kernel density at iteration XXXX, smoothed by inversion grid
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# ['model']['Keta_update_inv_XXXX'], eta kernel over kernel density at iteration XXXX, smoothed by inversion grid
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# ['1dinv']['vel_1dinv_inv_XXXX'], 2d velocity model at iteration XXXX, in 1d inversion mode
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# ['1dinv']['r_1dinv'], r coordinates (depth), in 1d inversion mode
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# ['1dinv']['t_1dinv'], t coordinates (epicenter distance), in 1d inversion mode
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# File: 'src_rec_file_step_XXXX.dat' or 'src_rec_file_forward.dat'. The synthetic traveltime data file.
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# File: 'final_model.h5'. Keys: ['eta'], ['xi'], ['vel'], the final model.
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# File: 'middle_model_step_XXXX.h5'. Keys: ['eta'], ['xi'], ['vel'], the model at step XXXX.
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# File: 'inversion_grid.txt'. The location of inversion grid nodes
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# File: 'objective_function.txt'. The objective function value at each iteration
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# File: 'out_data_sim_group_X'. Keys: ['src_YYYY']['time_field_inv_XXXX'], traveltime field of source YYYY at iteration XXXX;
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# ['src_YYYY']['adjoint_field_inv_XXXX'], adjoint field of source YYYY at iteration XXXX;
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# ['1dinv']['time_field_1dinv_YYYY_inv_XXXX'], 2d traveltime field of source YYYY at iteration XXXX, in 1d inversion mode
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# ['1dinv']['adjoint_field_1dinv_YYYY_inv_XXXX'], 2d adjoint field of source YYYY at iteration XXXX, in 1d inversion mode
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#################################################
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# inversion or forward modeling #
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#################################################
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# run mode
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# 0 for forward simulation only,
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# 1 for inversion
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# 2 for earthquake relocation
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# 3 for inversion + earthquake relocation
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# 4 for 1d model inversion
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run_mode: 2
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#################################################
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# relocation parameters setting #
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#################################################
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relocation: # update earthquake hypocenter and origin time (when run_mode : 2 and 3)
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min_Ndata: 4 # if the number of data of the earthquake is less than <min_Ndata>, the earthquake will not be relocated. defaut value: 4
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# relocation_strategy
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step_length : 0.01 # initial step length of relocation perturbation. 0.01 means maximum 1% perturbation for each iteration.
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step_length_decay : 0.9 # if objective function increase, step size -> step length * step_length_decay. default: 0.9
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rescaling_dep_lat_lon_ortime: [10.0, 15.0, 15.0, 1.0] # The perturbation is related to <rescaling_dep_lat_lon_ortime>. Unit: km,km,km,second
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max_change_dep_lat_lon_ortime: [10.0, 15.0, 15.0, 1.0] # the change of dep,lat,lon,ortime do not exceed max_change. Unit: km,km,km,second
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max_iterations : 201 # maximum number of iterations for relocation
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tol_gradient : 0.0001 # if the norm of gradient is smaller than the tolerance, the iteration of relocation terminates
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# -------------- using absolute traveltime data --------------
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abs_time:
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use_abs_time : true # 'yes' for using absolute traveltime data to update ortime and location; 'no' for not using (no need to set parameters in this section)
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# -------------- using common source differential traveltime data --------------
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cs_dif_time:
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use_cs_time : false # 'yes' for using common source differential traveltime data to update ortime and location; 'no' for not using (no need to set parameters in this section)
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# -------------- using common receiver differential traveltime data --------------
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cr_dif_time:
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use_cr_time : false # 'yes' for using common receiver differential traveltime data to update ortime and location; 'no' for not using (no need to set parameters in this section)
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@@ -0,0 +1,50 @@
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version: 3
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#################################################
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# computational domian #
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#################################################
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domain:
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min_max_dep: [-10, 50] # depth in km
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min_max_lat: [0, 2] # latitude in degree
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min_max_lon: [0, 2] # longitude in degree
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n_rtp: [61, 61, 61] # number of nodes in depth,latitude,longitude direction
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#################################################
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# traveltime data file path #
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#################################################
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source:
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src_rec_file: 1_src_rec_files/src_rec_config.dat # source receiver file path
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swap_src_rec: true # swap source and receiver
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#################################################
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# initial model file path #
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#################################################
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model:
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init_model_path: 2_models/model_ckb_N61_61_61.h5 # path to initial model file
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#################################################
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# parallel computation settings #
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#################################################
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parallel: # parameters for parallel computation
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n_sims: 8 # number of simultanoues runs (parallel the sources)
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ndiv_rtp: [1, 1, 1] # number of subdivision on each direction (parallel the computional domain)
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############################################
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# output file setting #
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############################################
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output_setting:
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output_dir: OUTPUT_FILES/OUTPUT_FILES_signal # path to output director (default is ./OUTPUT_FILES/)
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output_final_model: true # output merged final model (final_model.h5) or not.
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output_in_process: false # output model at each inv iteration or not.
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output_in_process_data: false # output src_rec_file at each inv iteration or not.
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output_file_format: 0
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#################################################
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# inversion or forward modeling #
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#################################################
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# run mode
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# 0 for forward simulation only,
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# 1 for inversion
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# 2 for earthquake relocation
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# 3 for inversion + earthquake relocation
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run_mode: 0
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29
examples/eg2_earthquake_location/README.md
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29
examples/eg2_earthquake_location/README.md
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# earthquake location
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This is a toy model to invert traveltimes for locating earthquakes (Figure 8a.)
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Reference:
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[1] 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.
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https://doi.org/10.48550/arXiv.2412.00031
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Python modules are required to initiate the inversion and to plot final results:
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- h5py
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- PyTomoAT
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- Pygmt
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- gmt
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Run this example:
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1. Run bash script `bash run_this_example.sh` to execute the test.
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2. After inversion, run `plot_output.py` to plot the results.
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The initial and true models:
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The location results:
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30
examples/eg2_earthquake_location/assign_gaussian_noise.py
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30
examples/eg2_earthquake_location/assign_gaussian_noise.py
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from pytomoatt.src_rec import SrcRec
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class AssignNoise:
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def __init__(self, in_fname, out_fname):
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self.in_fname = in_fname
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self.out_fname = out_fname
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self.sr = SrcRec.read(self.in_fname)
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def assign_noise_for_tt(self, noise_level=0.1):
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self.sr.add_noise(noise_level)
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def assign_noise_for_src(self, lat_pert=0.1, lon_pert=0.1, dep_pert=10, tau_pert=0.5):
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self.sr.add_noise_to_source(lat_pert, lon_pert, dep_pert, tau_pert)
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if __name__ == "__main__":
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in_fname = "OUTPUT_FILES/OUTPUT_FILES_signal/src_rec_file_forward.dat" # input source receiver file
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out_fname = "OUTPUT_FILES/OUTPUT_FILES_signal/src_rec_file_forward_errloc.dat" # output source receiver file
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sigma = 0.1 # noise level in seconds
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lat_pert = 0.1 # assign noise for latitude in degrees
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lon_pert = 0.1 # assign noise for longitude in degrees
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dep_pert = 10 # assign noise for depth in km
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tau_pert = 0.5 # assign noise for origin time in seconds
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# Initialize the instance
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an = AssignNoise(in_fname, out_fname)
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# Assign noise for travel time
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an.assign_noise_for_tt(sigma)
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# Assign noise for source
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an.assign_noise_for_src(lat_pert, lon_pert, dep_pert, tau_pert)
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# Write the output file
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an.sr.write(out_fname)
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254
examples/eg2_earthquake_location/plot_output.py
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254
examples/eg2_earthquake_location/plot_output.py
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# %%
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import pygmt
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pygmt.config(FONT="16p", IO_SEGMENT_MARKER="<<<")
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import os
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# %%
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from pytomoatt.model import ATTModel
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from pytomoatt.data import ATTData
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import numpy as np
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# %%
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# read models
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Ngrid = [61,61,61]
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data_file = '2_models/model_init_N%d_%d_%d.h5'%(Ngrid[0],Ngrid[1],Ngrid[2])
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par_file = '3_input_params/input_params_signal.yaml'
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model = ATTModel.read(data_file, par_file)
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initial_model = model.to_xarray()
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data_file = '2_models/model_ckb_N%d_%d_%d.h5'%(Ngrid[0],Ngrid[1],Ngrid[2])
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model = ATTModel.read(data_file, par_file)
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ckb_model = model.to_xarray()
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# initial model
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depth = 10.0
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vel_init = initial_model.interp_dep(depth, field='vel')
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start = [1.25,0]; end = [1.25,2]
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vel_init_sec = initial_model.interp_sec(start, end, field='vel', val = 1)
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# checkerboard model
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vel_ckb = ckb_model.interp_dep(depth, field='vel') # lon = [:,0], lat = [:,1], vel = [:,2]
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vel_ckb_sec = ckb_model.interp_sec(start, end, field='vel', val = 1)
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# anisotropic arrow
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samp_interval = 3
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length = 7
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width = 0.1
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ani_thd = 0.02
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ani_ckb_phi = ckb_model.interp_dep(depth, field='phi', samp_interval=samp_interval)
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ani_ckb_epsilon = ckb_model.interp_dep(depth, field='epsilon', samp_interval=samp_interval)
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ani_ckb = np.hstack([ani_ckb_phi, ani_ckb_epsilon[:,2].reshape(-1, 1)*length, np.ones((ani_ckb_epsilon.shape[0],1))*width]) # lon, lat, angle, length, width
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idx = np.where(ani_ckb_epsilon[:,2] > ani_thd)
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ani_ckb = ani_ckb[idx[0],:]
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try:
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os.mkdir('img')
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except:
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pass
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# %%
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# read src_rec_file for data
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from pytomoatt.src_rec import SrcRec
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sr = SrcRec.read('1_src_rec_files/src_rec_config.dat')
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station = sr.receivers[['stlo','stla','stel']].values.T
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true_loc = sr.sources[['evlo','evla','evdp']].values.T
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earthquake = true_loc
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sr = SrcRec.read('OUTPUT_FILES/OUTPUT_FILES_signal/src_rec_file_forward_errloc.dat')
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init_loc = sr.sources[['evlo','evla','evdp']].values.T
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# %%
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# categorize earthquakes
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ev_idx1 = []
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ev_idx2 = []
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ev_idx3 = []
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for i in range(earthquake.shape[1]):
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dep = earthquake[2,i]
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if dep < 15:
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ev_idx1.append(i)
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elif dep < 25:
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ev_idx2.append(i)
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elif dep < 35:
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ev_idx3.append(i)
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# %%
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# plot the model setting
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fig = pygmt.Figure()
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region = [0,2,0,2]
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frame = ["xa1","ya1"]
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projection = "M10c"
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spacing = 0.04
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vel_range = 20
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# -------------- initial model and earthquake location --------------
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fig.basemap(region=region, frame=["xa1","ya1","+tInitial model and locations"], projection=projection)
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# velocity perturbation
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pygmt.makecpt(cmap="../utils/svel13_chen.cpt", series=[-vel_range, vel_range], background=True, reverse=False)
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x = vel_ckb[:,0]; y = vel_ckb[:,1]; value = (vel_ckb[:,2] - vel_init[:,2])/vel_init[:,2] * 100
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grid = pygmt.surface(x=x, y=y, z=value, spacing=spacing,region=region)
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fig.grdimage(grid = grid)
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# earthquakes
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fig.plot(x = init_loc[0,ev_idx1], y = init_loc[1,ev_idx1], style = "c0.1c", fill = "red")
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fig.plot(x = init_loc[0,ev_idx2], y = init_loc[1,ev_idx2], style = "c0.1c", fill = "green")
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fig.plot(x = init_loc[0,ev_idx3], y = init_loc[1,ev_idx3], style = "c0.1c", fill = "black")
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# stations
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fig.plot(x = station[0,:], y = station[1,:], style = "t0.4c", fill = "blue", pen = "black", label = "Station")
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# anisotropic arrow
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fig.plot(ani_ckb, style='j', fill='yellow1', pen='0.5p,black')
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fig.shift_origin(xshift=11)
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fig.basemap(region=[0,40,0,2], frame=["xa20+lDepth (km)","ya1","Nswe"], projection="X2c/10c")
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x = vel_ckb_sec[:,3]; y = vel_ckb_sec[:,1]; value = (vel_ckb_sec[:,4] - vel_init_sec[:,4])/vel_init_sec[:,4] * 100
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grid = pygmt.surface(x=x, y=y, z=value, spacing="1/0.04",region=[0,40,0,2])
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fig.grdimage(grid = grid)
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# earthquakes
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fig.plot(x = init_loc[2,ev_idx1], y = init_loc[1,ev_idx1], style = "c0.1c", fill = "red")
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fig.plot(x = init_loc[2,ev_idx2], y = init_loc[1,ev_idx2], style = "c0.1c", fill = "green")
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fig.plot(x = init_loc[2,ev_idx3], y = init_loc[1,ev_idx3], style = "c0.1c", fill = "black")
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fig.shift_origin(xshift=4)
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# -------------- true model and earthquake location --------------
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fig.basemap(region=region, frame=["xa1","ya1","+tTrue model and locations"], projection=projection)
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# velocity perturbation
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pygmt.makecpt(cmap="../utils/svel13_chen.cpt", series=[-vel_range, vel_range], background=True, reverse=False)
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x = vel_ckb[:,0]; y = vel_ckb[:,1]; value = (vel_ckb[:,2] - vel_init[:,2])/vel_init[:,2] * 100
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grid = pygmt.surface(x=x, y=y, z=value, spacing=spacing,region=region)
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fig.grdimage(grid = grid)
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# earthquakes
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fig.plot(x = earthquake[0,ev_idx1], y = earthquake[1,ev_idx1], style = "c0.1c", fill = "red")
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fig.plot(x = earthquake[0,ev_idx2], y = earthquake[1,ev_idx2], style = "c0.1c", fill = "green")
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fig.plot(x = earthquake[0,ev_idx3], y = earthquake[1,ev_idx3], style = "c0.1c", fill = "black")
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# stations
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# fig.plot(x = loc_st[0,:], y = loc_st[1,:], style = "t0.4c", fill = "blue", pen = "black", label = "Station")
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# anisotropic arrow
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fig.plot(ani_ckb, style='j', fill='yellow1', pen='0.5p,black')
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||||
fig.shift_origin(xshift=11)
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fig.basemap(region=[0,40,0,2], frame=["xa20+lDepth (km)","ya1","Nswe"], projection="X2c/10c")
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x = vel_ckb_sec[:,3]; y = vel_ckb_sec[:,1]; value = (vel_ckb_sec[:,4] - vel_init_sec[:,4])/vel_init_sec[:,4] * 100
|
||||
grid = pygmt.surface(x=x, y=y, z=value, spacing="1/0.04",region=[0,40,0,2])
|
||||
fig.grdimage(grid = grid)
|
||||
|
||||
# earthquakes
|
||||
fig.plot(x = earthquake[2,ev_idx1], y = earthquake[1,ev_idx1], style = "c0.1c", fill = "red")
|
||||
fig.plot(x = earthquake[2,ev_idx2], y = earthquake[1,ev_idx2], style = "c0.1c", fill = "green")
|
||||
fig.plot(x = earthquake[2,ev_idx3], y = earthquake[1,ev_idx3], style = "c0.1c", fill = "black")
|
||||
|
||||
|
||||
# ------------------- colorbar -------------------
|
||||
fig.shift_origin(xshift=-11, yshift=-1.5)
|
||||
fig.colorbar(frame = ["a%f"%(vel_range),"x+ldlnVp (%)"], position="+e+w4c/0.3c+h")
|
||||
|
||||
fig.shift_origin(xshift=6, yshift=-1)
|
||||
fig.basemap(region=[0,1,0,1], frame=["wesn"], projection="X6c/1.5c")
|
||||
ani = [
|
||||
[0.2, 0.6, 45, 0.02*length, width], # lon, lat, phi, epsilon, size
|
||||
[0.5, 0.6, 45, 0.05*length, width],
|
||||
[0.8, 0.6, 45, 0.10*length, width],
|
||||
]
|
||||
fig.plot(ani, style='j', fill='yellow1', pen='0.5p,black')
|
||||
fig.text(text=["0.02", "0.05", "0.10"], x=[0.2,0.5,0.8], y=[0.2]*3, font="16p,Helvetica", justify="CM")
|
||||
fig.shift_origin(xshift= 11, yshift=2.5)
|
||||
|
||||
fig.show()
|
||||
fig.savefig('img/model_setting.png', dpi=300)
|
||||
|
||||
# %%
|
||||
# plot the location result
|
||||
|
||||
# read models
|
||||
tag = "loc"
|
||||
data_file = "OUTPUT_FILES/OUTPUT_FILES_%s/final_model.h5"%(tag)
|
||||
model = ATTModel.read(data_file, par_file)
|
||||
inv_model = model.to_xarray()
|
||||
vel_inv = inv_model.interp_dep(depth, field='vel') # lon = [:,0], lat = [:,1], vel = [:,2]
|
||||
x = vel_inv[:,0]; y = vel_inv[:,1]; value = (vel_inv[:,2] - vel_init[:,2])/vel_init[:,2] * 100
|
||||
vel_inv_sec = inv_model.interp_sec(start, end, field='vel', val = 1)
|
||||
x_sec = vel_inv_sec[:,3]; y_sec = vel_inv_sec[:,1]; value_sec = (vel_inv_sec[:,4] - vel_init_sec[:,4])/vel_init_sec[:,4] * 100
|
||||
|
||||
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_inv = ani_inv[idx[0],:]
|
||||
|
||||
sr = SrcRec.read('OUTPUT_FILES/OUTPUT_FILES_loc/src_rec_file_reloc_0201.dat')
|
||||
re_loc = sr.sources[['evlo','evla','evdp']].values.T
|
||||
|
||||
# plot the inversion result
|
||||
|
||||
fig = pygmt.Figure()
|
||||
|
||||
region = [0,2,0,2]
|
||||
frame = ["xa1","ya1","+tLocation results"]
|
||||
projection = "M10c"
|
||||
spacing = 0.04
|
||||
|
||||
vel_range = 20
|
||||
|
||||
# -------------- checkerboard model --------------
|
||||
fig.basemap(region=region, frame=frame, projection=projection)
|
||||
# velocity perturbation
|
||||
pygmt.makecpt(cmap="../utils/svel13_chen.cpt", series=[-vel_range, vel_range], background=True, reverse=False)
|
||||
x = vel_inv[:,0]; y = vel_inv[:,1]; value = (vel_inv[:,2] - vel_init[:,2])/vel_init[:,2] * 100
|
||||
grid = pygmt.surface(x=x, y=y, z=value, spacing=spacing,region=region)
|
||||
fig.grdimage(grid = grid)
|
||||
# earthquakes
|
||||
fig.plot(x = re_loc[0,ev_idx1], y = re_loc[1,ev_idx1], style = "c0.1c", fill = "red")
|
||||
fig.plot(x = re_loc[0,ev_idx2], y = re_loc[1,ev_idx2], style = "c0.1c", fill = "green")
|
||||
fig.plot(x = re_loc[0,ev_idx3], y = re_loc[1,ev_idx3], style = "c0.1c", fill = "black")
|
||||
|
||||
# stations
|
||||
# fig.plot(x = loc_st[0,:], y = loc_st[1,:], style = "t0.4c", fill = "blue", pen = "black", label = "Station")
|
||||
|
||||
# anisotropic arrow
|
||||
fig.plot(ani_inv, style='j', fill='yellow1', pen='0.5p,black')
|
||||
|
||||
fig.shift_origin(xshift=11)
|
||||
|
||||
fig.basemap(region=[0,40,0,2], frame=["xa20+lDepth (km)","ya1","Nswe"], projection="X2c/10c")
|
||||
x = vel_inv_sec[:,3]; y = vel_inv_sec[:,1]; value = (vel_inv_sec[:,4] - vel_init_sec[:,4])/vel_init_sec[:,4] * 100
|
||||
grid = pygmt.surface(x=x, y=y, z=value, spacing="1/0.04",region=[0,40,0,2])
|
||||
fig.grdimage(grid = grid)
|
||||
|
||||
# earthquakes
|
||||
fig.plot(x = re_loc[2,ev_idx1], y = re_loc[1,ev_idx1], style = "c0.1c", fill = "red")
|
||||
fig.plot(x = re_loc[2,ev_idx2], y = re_loc[1,ev_idx2], style = "c0.1c", fill = "green")
|
||||
fig.plot(x = re_loc[2,ev_idx3], y = re_loc[1,ev_idx3], style = "c0.1c", fill = "black")
|
||||
|
||||
# ------------------- colorbar -------------------
|
||||
fig.shift_origin(xshift=-11, yshift=-1.5)
|
||||
fig.colorbar(frame = ["a%f"%(vel_range),"x+ldlnVp (%)"], position="+e+w4c/0.3c+h")
|
||||
|
||||
fig.shift_origin(xshift=6, yshift=-1)
|
||||
fig.basemap(region=[0,1,0,1], frame=["wesn"], projection="X6c/1.5c")
|
||||
ani = [
|
||||
[0.2, 0.6, 45, 0.02*length, width], # lon, lat, phi, epsilon, size
|
||||
[0.5, 0.6, 45, 0.05*length, width],
|
||||
[0.8, 0.6, 45, 0.10*length, width],
|
||||
]
|
||||
fig.plot(ani, style='j', fill='yellow1', pen='0.5p,black')
|
||||
fig.text(text=["0.02", "0.05", "0.10"], x=[0.2,0.5,0.8], y=[0.2]*3, font="16p,Helvetica", justify="CM")
|
||||
fig.shift_origin(xshift= 11, yshift=2.5)
|
||||
|
||||
|
||||
fig.show()
|
||||
fig.savefig('img/model_%s.png'%(tag), dpi=300)
|
||||
|
||||
|
||||
61
examples/eg2_earthquake_location/prepare_input_files.py
Normal file
61
examples/eg2_earthquake_location/prepare_input_files.py
Normal file
@@ -0,0 +1,61 @@
|
||||
import numpy as np
|
||||
import os
|
||||
import sys
|
||||
try:
|
||||
from pytomoatt.checkerboard import Checker
|
||||
from pytomoatt.src_rec import SrcRec
|
||||
from pytomoatt.model import ATTModel
|
||||
except:
|
||||
print("ERROR: ATTModel not found. Please install pytomoatt first."
|
||||
"See https://tomoatt.github.io/PyTomoATT/installation.html for details.")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
class BuildInitialModel():
|
||||
def __init__(self, par_file="./3_input_params/input_params_signal.yaml", output_dir="2_models"):
|
||||
"""
|
||||
Build initial model for tomography inversion
|
||||
"""
|
||||
self.am = ATTModel(par_file)
|
||||
self.output_dir = output_dir
|
||||
|
||||
def build_initial_model(self, vel_min=5.0, vel_max=8.0):
|
||||
"""
|
||||
Build initial model for tomography inversion
|
||||
"""
|
||||
self.am.vel[self.am.depths < 0, :, :] = vel_min
|
||||
idx = np.where((0 <= self.am.depths) & (self.am.depths < 40.0))[0]
|
||||
self.am.vel[idx, :, :] = np.linspace(vel_min, vel_max, idx.size)[::-1][:, np.newaxis, np.newaxis]
|
||||
self.am.vel[self.am.depths >= 40.0, :, :] = vel_max
|
||||
|
||||
|
||||
def build_ckb_model(output_dir="2_models"):
|
||||
cbk = Checker(f'{output_dir}/model_init_N61_61_61.h5', para_fname="./3_input_params/input_params_signal.yaml")
|
||||
cbk.checkerboard(
|
||||
n_pert_x=2, n_pert_y=2, n_pert_z=2,
|
||||
pert_vel=0.2, pert_ani=0.1, ani_dir=60.0,
|
||||
lim_x=[0.5, 1.5], lim_y=[0.5, 1.5], lim_z=[0, 40]
|
||||
)
|
||||
cbk.write(f'{output_dir}/model_ckb_N61_61_61.h5')
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# download src_rec_file
|
||||
url = 'https://zenodo.org/records/14053821/files/src_rec_config.dat'
|
||||
path = "1_src_rec_files/src_rec_config.dat"
|
||||
os.makedirs(os.path.dirname(path), exist_ok=True)
|
||||
if not os.path.exists(path):
|
||||
sr = SrcRec.read(url)
|
||||
sr.write(path)
|
||||
|
||||
# build initial model
|
||||
output_dir = "2_models"
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
|
||||
bim = BuildInitialModel(output_dir=output_dir)
|
||||
bim.build_initial_model()
|
||||
bim.am.write('{}/model_init_N{:d}_{:d}_{:d}.h5'.format(bim.output_dir, *bim.am.n_rtp))
|
||||
|
||||
build_ckb_model(output_dir)
|
||||
|
||||
|
||||
27
examples/eg2_earthquake_location/run_this_example.sh
Normal file
27
examples/eg2_earthquake_location/run_this_example.sh
Normal file
@@ -0,0 +1,27 @@
|
||||
#!/bin/bash
|
||||
|
||||
|
||||
# Step 1: Generate necessary input files
|
||||
python prepare_input_files.py
|
||||
|
||||
# Step 2: Run forward modeling
|
||||
# # for WSL
|
||||
# mpirun -n 8 --allow-run-as-root --oversubscribe ../../build/bin/TOMOATT -i 3_input_params/input_params_signal.yaml
|
||||
# # for Linux
|
||||
# mpirun -n 8 ../../build/bin/TOMOATT -i 3_input_params/input_params_signal.yaml
|
||||
# for conda install
|
||||
mpirun -n 8 TOMOATT -i 3_input_params/input_params_signal.yaml
|
||||
|
||||
# Step 3: Assign data noise and location perturbation to the observational data
|
||||
python assign_gaussian_noise.py
|
||||
|
||||
# Step 4: Do relocation
|
||||
# # for WSL
|
||||
# mpirun -n 8 --allow-run-as-root --oversubscribe ../../build/bin/TOMOATT -i 3_input_params/input_params_loc.yaml
|
||||
# # for Linux
|
||||
# mpirun -n 8 ../../build/bin/TOMOATT -i 3_input_params/input_params_loc.yaml
|
||||
# for conda install
|
||||
mpirun -n 8 TOMOATT -i 3_input_params/input_params_loc.yaml
|
||||
|
||||
# Step 5 (Optional): Plot the results
|
||||
# python plot_output.py
|
||||
Reference in New Issue
Block a user