initial upload
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test/old_tests/.DS_Store
vendored
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test/old_tests/.DS_Store
vendored
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50
test/old_tests/heterogeneous_inv_test/input_params.yml
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50
test/old_tests/heterogeneous_inv_test/input_params.yml
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version : 2
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domain :
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min_max_dep : [-10.0, 10.0] # depth in km
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min_max_lat : [37.7,42.3] # latitude in degree
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min_max_lon : [22.7,27.3] # longitude in degree
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n_rtp : [10,50,50] # number of nodes
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source :
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src_rec_file : 'OUTPUT_FILES/src_rec_file_forward.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
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swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
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model :
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init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
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inversion :
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run_mode : 1 # 0 for forward simulation only, 1 for inversion
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optim_method : 2 # optimization method. 0 : "grad_descent", 1 : "halve-stepping", 2 : "lbfgs",
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max_iterations_inv : 20 # maximum number of inversion iterations
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step_size : 0.01 # step size for inversion
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# parameters for multiparametric inversion
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n_inversion_grid : 5 # number of inversion grid sets
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n_inv_dep_lat_lon : [5,20,20] # number of the base inversion grid points
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min_max_dep_inv : [-10.0, 10.0] # depth in km with R = 6371.0
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min_max_lat_inv : [37.7,43.3] # latitude in degree
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min_max_lon_inv : [22.7,28.3] # longitude in degree
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# parameter for halving-stepping or lbfgs
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max_sub_iterations : 10 # maximum number of sub-iterations
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#regularization_weight : 0.0 # regularization weight
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smooth_method: 0
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#l_smooth_rtp : [20,20,20] #
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parallel :
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n_sims : 1 # number of simultaneous run
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ndiv_rtp : [1,2,2] # number of subdomains
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nproc_sub : 2 # number of subprocess used for each subdomain
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calculation :
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convergence_tolerance : 1e-4
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max_iterations : 200
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stencil_order : 3 # 1 or 3
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sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
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output_setting :
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is_output_source_field : 0 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
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is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
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is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
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is_output_in_process : 1 # output the model parameters in each iteration. 1 for yes; 0 for no; default: 1
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34
test/old_tests/heterogeneous_inv_test/input_params_pre.yml
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34
test/old_tests/heterogeneous_inv_test/input_params_pre.yml
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version : 2
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domain :
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min_max_dep : [-10.0, 10.0] # depth in km
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min_max_lat : [37.7,42.3] # latitude in degree
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min_max_lon : [22.7,27.3] # longitude in degree
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n_rtp : [10,50,50] # number of nodes
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source :
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src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
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swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
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model :
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init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
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inversion :
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run_mode : 0 # 0 for forward simulation only, 1 for inversion
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n_inversion_grid : 1
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parallel :
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n_sims : 1 # number of simultaneous run
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ndiv_rtp : [1,2,2] # number of subdomains
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nproc_sub : 2 # number of subprocess used for each subdomain
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calculation :
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convergence_tolerance : 1e-4
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max_iterations : 500
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stencil_order : 3 # 1 or 3
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sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
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output_setting :
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is_output_source_field : 0 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
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is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
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is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
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441
test/old_tests/heterogeneous_inv_test/make_test_model.ipynb
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441
test/old_tests/heterogeneous_inv_test/make_test_model.ipynb
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14
test/old_tests/inversion/README.md
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14
test/old_tests/inversion/README.md
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# Inversion test
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This is a test setup for inversion calculation.
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1. Run all cells of `make_test_model.ipynb` for creating
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- source, receiver file
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- true model
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- initial model
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2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
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-> this will output src_rec_result.dat file which includes the arrival time at each station
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3. run TOMOATT in inversion mode with `input_params.yml`.
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66
test/old_tests/inversion/check_obj_func.ipynb
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66
test/old_tests/inversion/check_obj_func.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# check the change of objective values\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
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"fpath='objective_function.txt'\n",
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"\n",
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"objs=[]\n",
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"\n",
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"with open(fpath) as f:\n",
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" lines = f.readlines()\n",
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"\n",
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" for l in lines:\n",
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" if(l.startswith('i_inv')):\n",
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" continue\n",
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" objs.append(float(l.strip().split(',')[1]))\n",
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"\n",
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"\n",
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"plt.xlabel('iteration')\n",
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"plt.ylabel('objective function value')\n",
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"plt.plot(objs)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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||||
"source": []
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||||
}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.9.1 64-bit ('3.9.1')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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||||
"pygments_lexer": "ipython3",
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||||
"version": "3.9.1"
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||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "fbd0b2a7df497f398d93ab2f589d8a5daa3108cfb7ff2b90736653cca3aeadc0"
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||||
}
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||||
}
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||||
},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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185
test/old_tests/inversion/check_src_rec_file.ipynb
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185
test/old_tests/inversion/check_src_rec_file.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# read src_rec file and check its arrival time and distance from src to rec\n",
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"import numpy as np\n",
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"\n",
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"def read_src_rec_file(fpath):\n",
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"\n",
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" with open(fpath, \"r\") as f:\n",
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" lines = f.readlines()\n",
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"\n",
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" # list to store src lon lat\n",
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" src_pos = []\n",
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" # list to store rec lon lat\n",
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" rec_pos_tmp=[]\n",
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" rec_pos = []\n",
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"\n",
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" for line in lines:\n",
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" # src line if there are 13 elements\n",
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" if len(line.split()) == 13:\n",
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" # store source lon lat dep\n",
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" stlon = float(line.split()[8])\n",
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" stlat = float(line.split()[7])\n",
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" src_pos.append([stlon, stlat])\n",
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"\n",
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" nrec = float(line.split()[11])\n",
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" # rec line if there are 9 elements\n",
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" elif len(line.split()) == 9:\n",
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" # store receiver lon lat dep\n",
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" rclon = float(line.split()[4])\n",
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" rclat = float(line.split()[3])\n",
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" rctime= float(line.split()[8])\n",
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" # calc epicentral distance from src\n",
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" dist = np.sqrt((stlon-rclon)**2 + (stlat-rclat)**2)\n",
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" rec_pos_tmp.append([rclon, rclat, rctime, dist])\n",
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"\n",
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" nrec-=1\n",
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" else:\n",
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" raise ValueError(\"src_rec_test_out.dat file is not correct\")\n",
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"\n",
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" if nrec==0:\n",
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" rec_pos.append(rec_pos_tmp)\n",
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" # remove all rec_pos_tmp\n",
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" rec_pos_tmp = []\n",
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"\n",
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"\n",
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"\n",
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" src_pos = np.array(src_pos)\n",
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" rec_pos = np.array(rec_pos)\n",
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"\n",
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" return src_pos, rec_pos"
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]
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||||
},
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||||
{
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||||
"cell_type": "code",
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"execution_count": null,
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||||
"metadata": {},
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||||
"outputs": [],
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||||
"source": [
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||||
"src_pos_true, rec_pos_true = read_src_rec_file(\"./src_rec_test_out.dat\")\n",
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"src_pos_try, rec_pos_try = read_src_rec_file(\"./src_rec_test_out_out.dat\")"
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||||
]
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||||
},
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||||
{
|
||||
"cell_type": "code",
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"execution_count": null,
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||||
"metadata": {},
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||||
"outputs": [],
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||||
"source": [
|
||||
"# plot rec_pos for each src_pos with color by 3rd element\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"\n",
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"def plot_srcrec(src_pos, rec_pos):\n",
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"\n",
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" # selected source\n",
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" id_src = 1\n",
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||||
" \n",
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" fig, axs = plt.subplots(2,1,figsize=(10,10))\n",
|
||||
" \n",
|
||||
" # plot arrival time\n",
|
||||
" # src\n",
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" axs[0].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
" # rec\n",
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" axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=10, marker='o')\n",
|
||||
" \n",
|
||||
" # colorbar\n",
|
||||
" cbar = plt.colorbar(axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=100, marker='o'))\n",
|
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" cbar.set_label('arrival time')\n",
|
||||
" \n",
|
||||
" # plot epicentral distance\n",
|
||||
" # src\n",
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||||
" axs[1].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
" # rec\n",
|
||||
" axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=100, marker='o')\n",
|
||||
" \n",
|
||||
" # colorbar\n",
|
||||
" cbar = plt.colorbar(axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=10, marker='o'))\n",
|
||||
" cbar.set_label('epicentral distance')\n",
|
||||
" \n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"plot_srcrec(src_pos_true, rec_pos_true)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"plot_srcrec(src_pos_try, rec_pos_try)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_diff = rec_pos_true[:][:][2]-rec_pos_try[:][:][2]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_diff.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_true.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
51
test/old_tests/inversion/input_params.yml
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51
test/old_tests/inversion/input_params.yml
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|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-2.863,17.137] # depth in km
|
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min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
optim_method : 0 # optimization method. 0 : "grad_descent", 2 : "lbfgs", 1 : "halve-stepping"
|
||||
smooth_method : 0 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
max_iterations_inv : 100 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
# parameters for multiparametric inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [5,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-10.0, 10.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [37.7,42.3] # latitude in degree
|
||||
min_max_lon_inv : [22.7,27.3] # longitude in degree
|
||||
# parameters for laplacian smoothing
|
||||
l_smooth_rtp : [10,10,10] # smoothing coefficients for each direction
|
||||
regularization_weight : 1.0 # regularization weight NOTWORKING
|
||||
# parameter for halving-stepping or lbfgs
|
||||
max_sub_iterations : 100 # maximum number of sub-iterations
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
use_gpu : 0 # 0: CPU, 1: GPU
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-6
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
36
test/old_tests/inversion/input_params_pre.yml
Normal file
36
test/old_tests/inversion/input_params_pre.yml
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@@ -0,0 +1,36 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-2.863,17.137] # depth in km
|
||||
min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [2,1,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-6
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
348
test/old_tests/inversion/make_test_model.ipynb
Normal file
348
test/old_tests/inversion/make_test_model.ipynb
Normal file
@@ -0,0 +1,348 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"#R_earth = 6378.1370\n",
|
||||
"R_earth = 6371.0\n",
|
||||
"\n",
|
||||
"rr1=6361 \n",
|
||||
"rr2=6381\n",
|
||||
"tt1=(38.0-0.3)/180*math.pi\n",
|
||||
"tt2=(42.0+0.3)/180*math.pi\n",
|
||||
"pp1=(23.0-0.3)/180*math.pi\n",
|
||||
"pp2=(27.0+0.3)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [10,50,50]\n",
|
||||
"n_rtp.reverse()\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[2]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[0]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"s0 = 1.0/6.0\n",
|
||||
"slow_p=0.06\n",
|
||||
"ani_p=0.04\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"a_init = np.zeros(n_rtp)\n",
|
||||
"b_init = np.zeros(n_rtp)\n",
|
||||
"c_init = np.zeros(n_rtp)\n",
|
||||
"f_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"a_true = np.zeros(n_rtp)\n",
|
||||
"b_true = np.zeros(n_rtp)\n",
|
||||
"c_true = np.zeros(n_rtp)\n",
|
||||
"f_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ip,it,ir] = 0.0\n",
|
||||
" #xi_init[ip,it,ir] = 0.0\n",
|
||||
" zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)\n",
|
||||
" fun_init[ip,it,ir] = s0\n",
|
||||
" vel_init[ip,it,ir] = 1.0/s0\n",
|
||||
" a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]\n",
|
||||
" b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]\n",
|
||||
" c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]\n",
|
||||
" f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(2.0*math.pi*(tt[it]-38.0/180.0*math.pi)/(4.0/180.0*math.pi))*math.sin(2.0*math.pi*(pp[ip]-23.0/180.0*math.pi)/(4.0/180.0*math.pi))\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 120.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)\n",
|
||||
" fun_true[ip,it,ir] = s0/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir] \n",
|
||||
" a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]\n",
|
||||
" b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]\n",
|
||||
" c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]\n",
|
||||
" f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"#r_earth = 6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(R_earth-rr1,R_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init.T)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init.T)\n",
|
||||
"fout_init.create_dataset('zeta', data=zeta_init.T)\n",
|
||||
"fout_init.create_dataset('fun', data=fun_init.T)\n",
|
||||
"fout_init.create_dataset('fac_a', data=a_init.T)\n",
|
||||
"fout_init.create_dataset('fac_b', data=b_init.T)\n",
|
||||
"fout_init.create_dataset('fac_c', data=c_init.T)\n",
|
||||
"fout_init.create_dataset('fac_f', data=f_init.T)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init.T)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true.T)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true.T)\n",
|
||||
"fout_true.create_dataset('zeta', data=zeta_true.T)\n",
|
||||
"fout_true.create_dataset('fun', data=fun_true.T)\n",
|
||||
"fout_true.create_dataset('fac_a', data=a_true.T)\n",
|
||||
"fout_true.create_dataset('fac_b', data=b_true.T)\n",
|
||||
"fout_true.create_dataset('fac_c', data=c_true.T)\n",
|
||||
"fout_true.create_dataset('fac_f', data=f_true.T)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true.T)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(1145141919810)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 500\n",
|
||||
"n_rec = [30 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"nij_src = math.sqrt(n_src)\n",
|
||||
"nij_rec = math.sqrt(n_rec[0])\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create receiver coordinates\n",
|
||||
"elev_recs=[]\n",
|
||||
"lon_recs=[]\n",
|
||||
"lat_recs=[]\n",
|
||||
"rec_names=[]\n",
|
||||
"for i in range(n_rec[0]):\n",
|
||||
" #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
|
||||
" #elev_recs.append(0) # elevation in m\n",
|
||||
" #lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
|
||||
" #lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
|
||||
" rec_names.append(i)\n",
|
||||
" # regularly\n",
|
||||
" elev_recs.append(0.0)\n",
|
||||
" tmp_ilon = i%nij_rec\n",
|
||||
" tmp_ilat = int(i/nij_rec)\n",
|
||||
" lon_recs.append(pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec)\n",
|
||||
" lat_recs.append(tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" # random\n",
|
||||
" #dep = random.uniform((R_earth-rr1)*0.5,(R_earth-rr1)*0.98)\n",
|
||||
" #lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" # regularl\n",
|
||||
" dep = (R_earth-rr1)*0.9\n",
|
||||
" tmp_ilon = i_src%nij_src\n",
|
||||
" tmp_ilat = int(i_src/nij_src)\n",
|
||||
" lon = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_src\n",
|
||||
" lat = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_src\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = 0.0 #random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
" # regularly\n",
|
||||
" #elev_rec = -10.0\n",
|
||||
" #tmp_ilon = i_rec%nij_rec\n",
|
||||
" #tmp_ilat = int(i_rec/nij_rec)\n",
|
||||
" #lon_rec = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec\n",
|
||||
" #lat_rec = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec\n",
|
||||
"\n",
|
||||
" # \n",
|
||||
" elev_rec = elev_recs[i_rec]\n",
|
||||
" lon_rec = lon_recs[i_rec]\n",
|
||||
" lat_rec = lat_recs[i_rec]\n",
|
||||
" st_name_dummy = rec_names[i_rec]\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_rec,lat_rec,elev_rec])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
14
test/old_tests/inversion_2/README.md
Normal file
14
test/old_tests/inversion_2/README.md
Normal file
@@ -0,0 +1,14 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` for creating
|
||||
- source, receiver file
|
||||
- true model
|
||||
- initial model
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
-> this will output src_rec_result.dat file which includes the arrival time at each station
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`.
|
||||
|
||||
62
test/old_tests/inversion_2/check_obj_func.ipynb
Normal file
62
test/old_tests/inversion_2/check_obj_func.ipynb
Normal file
@@ -0,0 +1,62 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# check the change of objective values\n",
|
||||
"\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"fpath='objective_function.txt'\n",
|
||||
"\n",
|
||||
"objs=[]\n",
|
||||
"\n",
|
||||
"with open(fpath) as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" for l in lines:\n",
|
||||
" if(l.startswith('i_inv')):\n",
|
||||
" continue\n",
|
||||
" objs.append(float(l.strip().split(',')[1]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"plt.plot(objs)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"interpreter": {
|
||||
"hash": "fbd0b2a7df497f398d93ab2f589d8a5daa3108cfb7ff2b90736653cca3aeadc0"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
119
test/old_tests/inversion_2/check_src_rec_file.ipynb
Normal file
119
test/old_tests/inversion_2/check_src_rec_file.ipynb
Normal file
@@ -0,0 +1,119 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import sys\n",
|
||||
"sys.path.append(\"../../utils/\")\n",
|
||||
"\n",
|
||||
"from src_rec_file_helper import read_src_rec_file\n",
|
||||
"\n",
|
||||
"events_true = read_src_rec_file(\"./src_rec_test_out.dat\")\n",
|
||||
"events_calc = read_src_rec_file(\"./src_rec_test_out_out.dat\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# check objective function value\n",
|
||||
"v_obj = 0.0\n",
|
||||
"for i_ev in range(len(events_true)):\n",
|
||||
" for i_rec in range(len(events_true[i_ev].rec_list)):\n",
|
||||
" v_obj += abs(events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time)**2/2.0\n",
|
||||
"\n",
|
||||
"print(\"v_obj: \", v_obj)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# calculate summation of difference of arrival times at each receiver\n",
|
||||
"list_diff_v_obj = []\n",
|
||||
"for i_ev in range(len(events_true)):\n",
|
||||
" for i_rec in range(len(events_true[i_ev].rec_list)):\n",
|
||||
" #tmp_v_obj = abs(events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time)**2/2.0\n",
|
||||
" tmp_v_obj = events_true[i_ev].rec_list[i_rec].arr_time - events_calc[i_ev].rec_list[i_rec].arr_time\n",
|
||||
"\n",
|
||||
" if (i_ev == 0):\n",
|
||||
" list_diff_v_obj.append(tmp_v_obj)\n",
|
||||
" else:\n",
|
||||
" list_diff_v_obj[i_rec] += tmp_v_obj\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot list_diff_v_obj on map\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"# colormap by list_diff_v_obj\n",
|
||||
"cmap = plt.get_cmap('viridis')\n",
|
||||
"norm = plt.Normalize(vmin=min(list_diff_v_obj), vmax=max(list_diff_v_obj))\n",
|
||||
"\n",
|
||||
"print(\"min: \", min(list_diff_v_obj))\n",
|
||||
"print(\"max: \", max(list_diff_v_obj))\n",
|
||||
"\n",
|
||||
"list_lon = []\n",
|
||||
"list_lat = []\n",
|
||||
"\n",
|
||||
"for i_rec in range(len(events_true[0].rec_list)):\n",
|
||||
" list_lon.append(events_true[0].rec_list[i_rec].lon)\n",
|
||||
" list_lat.append(events_true[0].rec_list[i_rec].lat)\n",
|
||||
"\n",
|
||||
"plt.scatter(list_lon, list_lat, c=list_diff_v_obj, cmap=cmap, norm=norm)\n",
|
||||
"\n",
|
||||
"# color bar\n",
|
||||
"plt.colorbar()\n",
|
||||
"\n",
|
||||
"# tight \n",
|
||||
"plt.tight_layout()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
284
test/old_tests/inversion_2/compare_with_fortran_code.ipynb
Normal file
284
test/old_tests/inversion_2/compare_with_fortran_code.ipynb
Normal file
@@ -0,0 +1,284 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# compare result from TOMOATT and fortran code\n",
|
||||
"\n",
|
||||
"fpath_kernel_fort = './fortran/ega5/output/kernel_step1_sum'\n",
|
||||
"fpath_synth_fort = './fortran/ega5/output/syn_step1_event1' # Table\n",
|
||||
"fpath_adj_fort = './fortran/ega5/output/adj_step1_event1' # TableADJ\n",
|
||||
"fpath_out_tomoatt = './out_data_sim_0.h5'\n",
|
||||
"\n",
|
||||
"# grid information in fortran code\n",
|
||||
"nr = 55\n",
|
||||
"nt = 55\n",
|
||||
"np = 55\n",
|
||||
"npoints = nr*nt*np\n",
|
||||
"\n",
|
||||
"# division\n",
|
||||
"ndiv_r = 1 \n",
|
||||
"ndiv_t = 1 \n",
|
||||
"ndiv_p = 1 "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import h5py\n",
|
||||
"import numpy\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# read fortran test file and convert to numpy array\n",
|
||||
"def read_fortran_result_file(fpath):\n",
|
||||
" with open(fpath, 'r') as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
" lines = [line.strip() for line in lines]\n",
|
||||
" lines = [line for line in lines if line]\n",
|
||||
" lines = [line.split() for line in lines]\n",
|
||||
" lines = numpy.array(lines, dtype=numpy.float64)\n",
|
||||
" return lines\n",
|
||||
"\n",
|
||||
"fortran_data = read_fortran_result_file(fpath_kernel_fort)\n",
|
||||
"## change dimension of fortran data\n",
|
||||
"Ks_fort = fortran_data[:,3].reshape(nr, nt, np)\n",
|
||||
"Kxi_fort = fortran_data[:,4].reshape(nr, nt, np)\n",
|
||||
"Keta_fort = fortran_data[:,5].reshape(nr, nt, np)\n",
|
||||
"\n",
|
||||
"fortran_synth_data = read_fortran_result_file(fpath_synth_fort).reshape(nr, nt, np)\n",
|
||||
"fortran_adj_data = read_fortran_result_file(fpath_adj_fort).reshape(nr, nt, np)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# read h5 data\n",
|
||||
"import sys\n",
|
||||
"sys.path.append(\"../../utils/\")\n",
|
||||
"\n",
|
||||
"from tomoatt_data_retrieval import get_data_from_h5\n",
|
||||
"\n",
|
||||
"#Ks_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Ks_update_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p, verbose=True)\n",
|
||||
"#Kxi_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Kxi_update_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)\n",
|
||||
"#Keta_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Keta_update_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)\n",
|
||||
"\n",
|
||||
"Ks_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Ks_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p, verbose=True)\n",
|
||||
"Kxi_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Kxi_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)\n",
|
||||
"Keta_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/Keta_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)\n",
|
||||
"\n",
|
||||
"Syn_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/T_res_src_0_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)\n",
|
||||
"Adj_tomoatt = get_data_from_h5(fpath_out_tomoatt, \"Data/adjoint_field_src_0_inv_0000\", nr, nt, np, ndiv_r, ndiv_t, ndiv_p)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot slice of Ks_inv\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import matplotlib.animation as animation\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def plot_slice(data_es, data_fort, slice_ax, id_slice, contour=False, make_anime=False, tag=\"\"):\n",
|
||||
"\n",
|
||||
" if (slice_ax == 'r'):\n",
|
||||
" data_es_v = data_es[ id_slice, :, :]\n",
|
||||
" data_fort_v = data_fort[id_slice, :, :]\n",
|
||||
" elif (slice_ax == 't'):\n",
|
||||
" data_es_v = data_es[ :, id_slice, :]\n",
|
||||
" data_fort_v = data_fort[:, id_slice, :]\n",
|
||||
" elif (slice_ax == 'p'):\n",
|
||||
" data_es_v = data_es[ :, :, id_slice]\n",
|
||||
" data_fort_v = data_fort[:, :, id_slice]\n",
|
||||
" else:\n",
|
||||
" print(\"Error: slice_ax should be 'r', 't' or 'p'\")\n",
|
||||
" return\n",
|
||||
"\n",
|
||||
" # use the same color range for both tomoatt and fortran \n",
|
||||
" combined_data = numpy.array([data_es_v.flatten(),data_fort_v.flatten()])\n",
|
||||
" #Get the min and max of all your data\n",
|
||||
" _min, _max = numpy.amin(combined_data), numpy.amax(combined_data)\n",
|
||||
" # make the color range symmetric\n",
|
||||
" if (abs(_min) > abs(_max)):\n",
|
||||
" if(_min < 0):\n",
|
||||
" _max = -_min\n",
|
||||
" else:\n",
|
||||
" _min = -_max\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" # make the color range symmetric\n",
|
||||
" diff_data = data_es_v-data_fort_v\n",
|
||||
" _min_diff, _max_diff = numpy.amin(diff_data), numpy.amax(diff_data)\n",
|
||||
" if (abs(_min_diff) > abs(_max_diff)):\n",
|
||||
" if (_min_diff < 0):\n",
|
||||
" _max_diff = -_min_diff\n",
|
||||
" else:\n",
|
||||
" _min_diff = -_max_diff\n",
|
||||
"\n",
|
||||
" #cmap1=\"viridis\"\n",
|
||||
" cmap1=\"seismic\"\n",
|
||||
" cmap2=\"seismic\"\n",
|
||||
"\n",
|
||||
" plt.figure(figsize=(20,10))\n",
|
||||
"\n",
|
||||
" plt.subplot(1,3,1)\n",
|
||||
" plt.imshow(data_es_v, cmap=cmap1, vmin=_min, vmax=_max)\n",
|
||||
" plt.colorbar()\n",
|
||||
" if(contour):\n",
|
||||
" plt.contour(data_es_v, colors='k', linewidths=0.5)\n",
|
||||
" plt.title('result_tomoatt')\n",
|
||||
"\n",
|
||||
" plt.subplot(1,3,2)\n",
|
||||
" plt.imshow(data_fort_v, cmap=cmap1, vmin=_min, vmax=_max)\n",
|
||||
" plt.colorbar()\n",
|
||||
" if(contour): \n",
|
||||
" plt.contour(data_fort_v, colors='k', linewidths=0.5)\n",
|
||||
" plt.title('result_fort')\n",
|
||||
" \n",
|
||||
" plt.subplot(1,3,3)\n",
|
||||
" plt.imshow(diff_data, cmap=cmap2, vmin=_min_diff, vmax=_max_diff)\n",
|
||||
" plt.colorbar()\n",
|
||||
" if(contour):\n",
|
||||
" plt.contour(diff_data, colors='k', linewidths=0.5) \n",
|
||||
" plt.title('tomoatt-fort')\n",
|
||||
"\n",
|
||||
" if (not make_anime):\n",
|
||||
" plt.show()\n",
|
||||
" else:\n",
|
||||
" plt.savefig(\"out_\"+tag+\"_\"+slice_ax+str(id_slice).zfill(3)+\".png\")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"plot_slice(Syn_tomoatt, fortran_synth_data, 'r', 20, contour=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"\n",
|
||||
"def anime_slices(data_es, data_fort, slice_ax, tag):\n",
|
||||
"\n",
|
||||
" if (slice_ax == 'r'):\n",
|
||||
" n = nr\n",
|
||||
" elif (slice_ax == 't'):\n",
|
||||
" n = nt\n",
|
||||
" elif (slice_ax == 'p'):\n",
|
||||
" n = np\n",
|
||||
"\n",
|
||||
" for i in range(0, n):\n",
|
||||
" plot_slice(data_es, data_fort, slice_ax, i, contour=True, make_anime=True, tag=tag)\n",
|
||||
"\n",
|
||||
" ## make png files to gif\n",
|
||||
" import subprocess\n",
|
||||
" subprocess.call([\"convert\", \"-delay\", \"20\", \"-loop\", \"0\", \"out_{}_{}*.png\".format(tag,slice_ax), \"out_{}_{}.gif\".format(tag,slice_ax)])\n",
|
||||
" # erase png files\n",
|
||||
" for i in range(0, nr):\n",
|
||||
" subprocess.call([\"rm\", \"out_{}_{}\".format(tag,slice_ax)+str(i).zfill(3)+\".png\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"anime_slices(Ks_tomoatt, Ks_fort, 'r', 'Ks')\n",
|
||||
"anime_slices(Ks_tomoatt, Ks_fort, 't', 'Ks')\n",
|
||||
"anime_slices(Ks_tomoatt, Ks_fort, 'p', 'Ks')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"anime_slices(Adj_tomoatt, fortran_adj_data,'r', 'Adj')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"anime_slices(Keta_tomoatt, Keta_fort, 'r', 'Keta')\n",
|
||||
"anime_slices(Keta_tomoatt, Keta_fort, 't', 'Keta')\n",
|
||||
"anime_slices(Keta_tomoatt, Keta_fort, 'p', 'Keta')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"anime_slices(Kxi_tomoatt, Kxi_fort, 'r', 'Kxi')\n",
|
||||
"anime_slices(Kxi_tomoatt, Kxi_fort, 't', 'Kxi')\n",
|
||||
"anime_slices(Kxi_tomoatt, Kxi_fort, 'p', 'Kxi')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"anime_slices(Adj_tomoatt, fortran_adj_data, 'r', 'adj')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
3
test/old_tests/inversion_2/fortran/Readme.txt
Normal file
3
test/old_tests/inversion_2/fortran/Readme.txt
Normal file
@@ -0,0 +1,3 @@
|
||||
mpif90 ega5_sphe_3d_inversion_Tong_3Dinv.f90 -o a5.out
|
||||
|
||||
mpirun -n 4 a5.out
|
||||
501
test/old_tests/inversion_2/fortran/ega5/input/EARTHQUAKES.txt
Normal file
501
test/old_tests/inversion_2/fortran/ega5/input/EARTHQUAKES.txt
Normal file
@@ -0,0 +1,501 @@
|
||||
500
|
||||
12.902894 37.503373 16.794572
|
||||
17.416074 36.974148 25.587149
|
||||
10.553441 48.572870 29.755519
|
||||
17.050082 30.582756 20.557365
|
||||
7.733536 30.049830 22.686053
|
||||
2.695465 45.678252 36.050257
|
||||
19.018349 30.835213 33.695062
|
||||
16.538200 39.559879 22.351080
|
||||
2.947435 37.234474 24.550463
|
||||
15.739527 49.857044 16.506392
|
||||
15.732578 34.182860 27.127186
|
||||
1.296549 48.107962 29.948977
|
||||
14.587690 39.140723 23.153653
|
||||
18.135532 45.517829 17.105875
|
||||
8.364121 30.479830 15.883796
|
||||
9.211189 38.133248 17.858524
|
||||
4.272898 31.194404 18.573422
|
||||
6.948694 35.954361 24.462624
|
||||
12.746088 49.850406 26.847644
|
||||
11.313107 45.103047 16.301263
|
||||
3.313507 46.477589 36.875331
|
||||
10.145642 42.073024 18.769733
|
||||
8.250413 48.900277 19.475522
|
||||
13.804441 49.786255 16.530966
|
||||
17.835237 45.927679 19.912836
|
||||
11.877357 33.654921 22.852455
|
||||
12.871971 34.707392 21.890595
|
||||
4.097522 34.532987 27.568581
|
||||
17.874029 34.484387 34.692491
|
||||
3.866172 33.865449 28.496058
|
||||
16.252330 41.105672 19.464576
|
||||
1.213538 36.013973 17.977264
|
||||
14.955385 45.399043 29.827500
|
||||
17.469489 35.163250 19.273657
|
||||
7.375320 32.817054 28.313777
|
||||
18.585662 33.143956 25.800265
|
||||
15.518612 34.328928 29.752072
|
||||
18.309939 33.218516 38.096180
|
||||
5.752131 32.762387 39.124230
|
||||
12.471990 48.600499 37.709010
|
||||
8.119302 41.058539 27.574594
|
||||
13.473451 36.710096 33.310765
|
||||
12.096579 45.910913 20.602681
|
||||
12.291621 35.421838 19.609690
|
||||
6.722855 34.197625 22.922348
|
||||
19.977008 33.357824 20.801610
|
||||
14.042122 42.609560 36.961508
|
||||
8.278199 33.440638 35.377468
|
||||
10.130480 41.237552 26.524442
|
||||
9.874228 41.667609 22.900117
|
||||
2.528995 40.838610 35.938716
|
||||
15.334613 43.507392 36.217644
|
||||
2.660098 44.120069 32.041887
|
||||
1.861117 38.659778 36.102099
|
||||
17.497575 45.676303 27.354341
|
||||
11.287530 40.851293 33.379047
|
||||
18.006903 38.149825 25.683572
|
||||
9.641227 30.509291 32.005355
|
||||
11.281402 38.301783 26.210378
|
||||
17.511430 43.700541 20.496900
|
||||
6.279207 49.780686 35.342213
|
||||
10.691969 45.580664 36.011519
|
||||
15.409820 38.320676 17.830344
|
||||
19.051727 44.632362 37.180772
|
||||
1.812418 37.134760 37.694988
|
||||
4.160294 33.803068 37.492413
|
||||
19.990846 44.087650 38.916613
|
||||
6.919528 36.705624 30.282383
|
||||
3.762207 33.859941 23.084520
|
||||
6.696542 31.799267 15.983610
|
||||
5.207515 43.495341 36.539506
|
||||
15.760515 33.837372 18.996584
|
||||
16.401076 40.346859 29.422924
|
||||
3.985079 48.258603 32.826637
|
||||
16.886675 48.716436 23.605320
|
||||
18.974327 46.091270 22.697943
|
||||
7.384952 38.441961 16.463244
|
||||
4.231388 42.800608 22.558010
|
||||
3.169625 49.753544 33.780253
|
||||
3.741493 42.843651 38.277171
|
||||
1.703036 35.504006 28.680233
|
||||
2.556739 31.467144 23.718764
|
||||
8.546980 41.234760 31.150894
|
||||
13.221493 40.941614 33.480616
|
||||
6.837920 34.912584 35.820479
|
||||
7.716762 41.133360 20.876900
|
||||
10.321416 31.362250 29.092427
|
||||
17.855166 45.569227 19.744126
|
||||
5.414400 45.949803 24.029219
|
||||
10.622310 33.633958 37.349613
|
||||
18.821079 45.259309 23.690669
|
||||
6.400983 42.879048 20.743236
|
||||
10.339512 44.689643 20.088403
|
||||
14.157235 42.069607 38.833834
|
||||
17.014583 34.928036 31.302363
|
||||
12.827352 36.255275 22.938120
|
||||
7.405344 48.287391 34.564176
|
||||
3.771071 43.293532 28.422367
|
||||
11.910684 48.348929 36.441739
|
||||
3.053959 43.737186 36.600389
|
||||
8.579958 40.581127 25.851314
|
||||
11.931197 31.720220 17.810105
|
||||
7.425585 44.628309 34.089390
|
||||
1.517343 49.451598 36.749768
|
||||
13.373374 37.648809 36.512094
|
||||
4.490529 47.682461 26.286905
|
||||
17.470296 43.349799 16.006251
|
||||
19.343889 44.865620 31.299373
|
||||
15.455612 39.569737 21.775167
|
||||
13.382569 38.684806 37.606354
|
||||
16.876219 37.640250 22.490769
|
||||
5.007780 43.252308 31.761110
|
||||
14.917810 48.036944 16.404019
|
||||
18.211096 33.840776 16.319922
|
||||
7.586946 30.429530 17.767477
|
||||
15.527441 36.791267 32.576167
|
||||
8.395652 47.363883 30.734555
|
||||
8.300918 45.773041 18.973032
|
||||
12.811946 37.078433 31.654726
|
||||
11.271027 44.367770 23.614827
|
||||
7.883254 33.508117 25.081344
|
||||
9.318537 34.252752 21.126458
|
||||
10.125988 49.407886 23.732711
|
||||
15.231482 31.012657 38.326734
|
||||
17.583612 46.667417 35.223383
|
||||
3.975712 45.446574 19.293018
|
||||
6.378385 47.601238 37.559922
|
||||
2.237225 46.922084 15.276371
|
||||
18.881117 47.018476 32.117860
|
||||
7.601149 37.424848 33.048987
|
||||
1.545623 35.528771 31.054720
|
||||
15.305942 41.902726 32.920003
|
||||
8.780450 43.137000 29.771781
|
||||
15.653881 33.574476 22.550923
|
||||
8.374878 42.226796 29.428747
|
||||
1.649332 37.516438 29.602287
|
||||
15.471741 42.579812 34.244173
|
||||
14.121526 31.968351 35.539179
|
||||
19.951984 31.884994 38.930168
|
||||
5.686047 46.021632 37.620089
|
||||
3.356280 35.028285 27.812111
|
||||
17.282928 32.916989 20.503907
|
||||
17.587365 30.437778 27.868687
|
||||
16.846272 32.526293 23.686783
|
||||
5.595438 46.916388 30.602188
|
||||
10.617813 47.056847 29.509244
|
||||
3.472421 46.734969 23.827490
|
||||
9.450474 39.510548 26.858533
|
||||
7.050903 31.802893 18.651294
|
||||
16.740378 42.673295 22.941474
|
||||
8.748832 49.086459 28.498236
|
||||
11.101980 48.419839 33.467477
|
||||
1.821840 40.425959 24.967524
|
||||
18.807331 49.210102 23.627239
|
||||
16.048152 33.431415 27.275778
|
||||
4.156495 37.028503 23.441579
|
||||
8.252786 43.619866 31.044609
|
||||
6.039243 44.924797 25.445324
|
||||
15.698418 36.891680 31.709361
|
||||
13.305460 31.432069 28.565380
|
||||
1.884098 33.514374 39.083138
|
||||
19.784318 48.068758 33.412684
|
||||
10.067793 43.703751 38.394139
|
||||
9.332467 39.505090 19.017737
|
||||
12.280919 46.423916 38.722269
|
||||
18.443031 39.348801 27.023964
|
||||
15.761264 48.206337 22.708882
|
||||
7.403360 37.157790 15.624682
|
||||
11.901780 46.996568 29.408969
|
||||
19.234729 44.636488 39.127281
|
||||
4.699343 31.480019 22.985463
|
||||
8.029268 33.651500 17.282239
|
||||
9.408798 39.483198 37.726002
|
||||
2.995543 45.341282 28.914835
|
||||
1.469270 43.894101 35.258155
|
||||
17.054291 30.978729 17.580649
|
||||
5.151633 42.357135 21.048084
|
||||
11.523488 48.279981 20.451448
|
||||
12.625369 47.910449 23.809322
|
||||
10.805510 39.289972 33.099199
|
||||
16.688680 31.235778 31.772384
|
||||
5.872404 46.921761 20.735459
|
||||
7.760370 49.248566 27.412126
|
||||
14.981766 48.345084 22.449809
|
||||
17.494891 42.556305 17.939339
|
||||
16.883756 35.789221 26.232745
|
||||
18.320859 32.768764 34.301897
|
||||
17.639973 41.691055 20.038187
|
||||
9.699485 49.507576 29.079033
|
||||
18.107852 35.136726 29.376171
|
||||
18.308439 37.395076 27.395968
|
||||
7.807415 35.196537 36.702486
|
||||
19.870463 31.937476 26.900138
|
||||
3.831742 44.590580 18.565134
|
||||
15.201851 32.646130 39.026955
|
||||
15.828158 47.973824 36.504196
|
||||
13.003291 37.834748 30.167337
|
||||
6.392706 37.452325 18.574045
|
||||
16.906282 42.459442 35.050055
|
||||
13.809721 39.226894 19.719641
|
||||
2.349331 48.568978 36.858088
|
||||
13.463109 31.025621 32.611917
|
||||
7.791103 35.619114 35.466085
|
||||
15.908805 31.883312 36.337440
|
||||
12.117860 40.626769 15.503395
|
||||
17.224971 30.288926 20.225713
|
||||
7.769806 32.781915 20.240085
|
||||
19.515691 32.790366 18.423108
|
||||
13.086107 35.997238 32.187432
|
||||
19.583843 46.680117 23.645876
|
||||
5.856651 40.007246 21.179095
|
||||
7.862932 44.479540 23.893157
|
||||
6.880727 30.486859 36.304971
|
||||
12.890612 39.620341 15.500047
|
||||
17.079175 38.401798 27.785445
|
||||
5.828536 41.348587 16.106890
|
||||
16.937460 42.816015 36.720915
|
||||
3.914160 30.441916 38.949482
|
||||
19.655249 45.167885 21.419356
|
||||
5.977111 38.508239 20.391821
|
||||
6.927604 39.621611 32.875926
|
||||
18.361222 45.590869 38.069800
|
||||
10.260030 43.346131 15.879682
|
||||
2.192603 39.046662 33.248710
|
||||
19.085453 37.873403 16.629225
|
||||
12.101016 38.044051 24.990450
|
||||
5.819428 32.772253 26.474392
|
||||
12.724981 46.690291 27.925452
|
||||
18.061294 42.771723 33.725329
|
||||
14.506720 47.805098 26.622413
|
||||
19.850651 49.189715 25.849751
|
||||
15.219038 43.463470 25.041924
|
||||
19.886991 34.051333 32.426005
|
||||
7.117638 32.476564 32.376542
|
||||
5.495352 36.502620 28.691081
|
||||
16.996145 40.153394 37.204504
|
||||
6.456862 33.696229 34.883926
|
||||
2.330674 33.891702 15.484274
|
||||
16.654256 35.373110 33.898747
|
||||
5.038885 38.192102 27.689718
|
||||
14.123672 33.761702 24.479974
|
||||
1.429166 47.744844 31.788410
|
||||
4.269137 39.186264 18.096003
|
||||
2.289546 40.394737 27.797130
|
||||
8.634843 49.702312 16.408445
|
||||
4.519147 37.133705 18.956423
|
||||
15.655447 42.736719 21.384360
|
||||
12.749631 32.600550 38.708210
|
||||
4.951746 46.823971 36.767247
|
||||
9.331854 35.692199 21.771833
|
||||
10.011062 46.663543 24.723024
|
||||
19.949108 42.198244 27.340252
|
||||
10.252827 47.219953 25.322984
|
||||
16.510059 43.107901 28.874568
|
||||
6.363226 49.090611 17.454213
|
||||
10.635868 40.297072 33.028443
|
||||
16.850642 38.133906 27.489172
|
||||
1.209319 37.893652 34.507359
|
||||
12.115913 34.227874 36.364014
|
||||
12.821762 39.440078 33.040301
|
||||
18.591223 39.525593 31.873724
|
||||
8.071489 49.360508 16.522758
|
||||
8.888324 42.368580 26.650131
|
||||
8.889626 41.127943 35.902008
|
||||
10.999334 37.031617 39.494656
|
||||
18.362983 30.378271 18.297875
|
||||
4.302350 36.174539 25.849816
|
||||
7.203800 35.926694 33.803271
|
||||
5.955434 30.625004 18.539309
|
||||
18.701156 48.114168 36.495495
|
||||
9.310080 31.778387 24.469818
|
||||
4.443713 48.914441 17.652480
|
||||
6.915923 33.492221 30.512492
|
||||
12.953648 47.034138 17.407188
|
||||
13.014381 38.565701 16.404760
|
||||
3.750504 34.237353 36.468920
|
||||
14.823263 48.440372 22.486555
|
||||
15.668423 46.749729 32.080923
|
||||
15.249817 31.028147 15.608834
|
||||
13.264813 47.340345 31.103057
|
||||
15.198867 35.515848 16.671581
|
||||
9.743653 41.383808 30.090270
|
||||
13.220311 46.330492 36.129090
|
||||
3.174404 32.263913 36.140707
|
||||
6.044751 33.274473 15.721678
|
||||
11.565608 35.746820 22.653814
|
||||
16.179206 44.677125 24.020450
|
||||
11.327136 44.811048 32.693529
|
||||
1.636618 40.444103 18.356178
|
||||
10.744547 37.150505 16.214572
|
||||
13.261026 34.105829 21.999317
|
||||
3.868859 49.216692 21.453701
|
||||
18.240428 30.304513 30.673916
|
||||
7.072615 35.062618 26.710350
|
||||
9.121655 48.655297 29.967281
|
||||
5.855663 35.811613 27.420149
|
||||
12.000977 43.413023 15.537291
|
||||
6.564213 36.838226 35.870052
|
||||
7.714274 42.313338 28.048145
|
||||
2.081489 43.751865 27.701850
|
||||
8.319217 33.115678 38.739537
|
||||
14.511302 34.703210 16.585363
|
||||
9.035614 36.808248 20.909689
|
||||
14.228832 44.449462 15.947576
|
||||
10.282913 49.531593 19.906303
|
||||
17.589859 47.123318 23.446360
|
||||
4.864052 37.595184 15.336005
|
||||
5.554797 45.565313 38.282334
|
||||
10.528200 42.619743 24.326508
|
||||
11.040215 46.010982 22.617869
|
||||
11.404083 46.772047 20.275623
|
||||
8.466629 43.802511 26.377092
|
||||
14.969797 31.351324 25.339695
|
||||
14.235184 33.858954 37.025746
|
||||
8.455785 49.863795 33.265439
|
||||
8.889406 35.667726 17.308049
|
||||
6.681788 37.412732 15.346280
|
||||
8.976410 34.648739 17.568041
|
||||
10.814533 44.752360 29.627384
|
||||
10.199468 40.546340 32.494767
|
||||
14.496903 45.258427 38.066645
|
||||
3.094126 35.259604 16.746947
|
||||
8.520395 42.659554 15.880581
|
||||
17.611133 41.555600 18.232809
|
||||
14.251795 33.115916 20.736805
|
||||
7.514731 30.399115 21.351999
|
||||
5.196915 45.397866 34.915807
|
||||
19.166354 32.396496 21.352377
|
||||
13.151796 40.555799 27.727383
|
||||
5.350548 46.598504 34.378491
|
||||
9.529635 40.571371 18.426558
|
||||
9.126816 41.898209 17.050111
|
||||
13.802897 32.953515 28.238527
|
||||
15.418929 34.298935 26.833731
|
||||
12.574792 35.492734 26.555897
|
||||
16.938654 44.491948 25.265210
|
||||
10.924080 48.518974 17.175958
|
||||
7.117455 42.434404 23.654994
|
||||
14.009338 36.036521 39.017975
|
||||
19.349324 30.799935 19.716167
|
||||
14.201462 37.024155 38.578311
|
||||
2.822673 33.994394 34.302821
|
||||
13.892456 32.962351 32.359032
|
||||
15.995095 43.754437 29.772219
|
||||
12.968758 32.410285 24.381215
|
||||
1.583361 48.689008 24.016421
|
||||
15.389693 46.555314 19.407358
|
||||
17.453486 39.698530 32.665472
|
||||
12.941524 30.636925 27.452996
|
||||
13.213848 32.944137 23.119204
|
||||
5.801494 40.680483 39.987076
|
||||
16.748570 32.170913 15.378249
|
||||
5.500054 38.628247 24.922452
|
||||
9.008471 31.774374 37.808194
|
||||
14.855098 47.897280 39.249556
|
||||
18.168511 33.566407 22.346673
|
||||
17.753149 42.913741 33.127159
|
||||
19.795910 35.010497 18.833259
|
||||
13.418894 37.999490 18.797014
|
||||
10.696075 37.767208 37.509466
|
||||
1.516162 41.220767 36.769994
|
||||
9.791821 47.293788 32.327841
|
||||
15.542095 41.085072 23.263423
|
||||
16.094111 33.695693 15.819606
|
||||
11.757946 39.421142 30.979153
|
||||
16.568937 34.064155 18.969278
|
||||
6.911632 36.546812 20.978434
|
||||
4.881109 32.834115 39.250059
|
||||
14.023054 45.882062 37.160694
|
||||
9.816248 46.742746 29.781763
|
||||
8.756145 37.174411 24.408729
|
||||
17.588240 44.192292 26.619717
|
||||
17.340343 41.790910 28.580176
|
||||
12.088289 45.478525 27.897123
|
||||
2.586683 37.906181 27.284716
|
||||
14.494787 31.239448 15.065949
|
||||
19.880752 30.337209 16.025088
|
||||
12.823786 43.458027 18.855097
|
||||
15.293022 31.406674 37.847072
|
||||
13.980302 44.345304 18.989914
|
||||
8.991872 32.283652 15.894826
|
||||
10.306169 44.491996 15.351453
|
||||
9.244054 31.064154 35.461811
|
||||
11.066989 35.074635 21.009033
|
||||
9.996705 35.829850 28.967240
|
||||
11.044099 39.587919 35.338766
|
||||
1.917792 49.787496 20.053103
|
||||
1.898804 31.727660 26.029601
|
||||
17.236757 44.662413 28.599031
|
||||
8.003001 41.530145 34.147378
|
||||
11.296640 31.640054 29.667642
|
||||
7.470842 38.590285 16.251505
|
||||
4.120357 40.312343 30.229225
|
||||
8.168395 39.952977 27.957050
|
||||
14.557243 45.490199 23.005864
|
||||
8.675602 35.746172 28.944592
|
||||
13.436976 32.236888 28.823008
|
||||
17.809797 33.690628 26.829731
|
||||
8.031168 39.495328 32.948914
|
||||
14.566420 42.285006 32.930929
|
||||
10.051800 39.544345 25.797573
|
||||
15.312497 35.367693 24.154386
|
||||
2.101328 37.582577 35.819286
|
||||
14.200961 38.741432 22.349646
|
||||
17.750624 33.199228 15.433538
|
||||
5.105492 42.003092 30.932790
|
||||
10.710424 46.645944 31.550315
|
||||
4.863936 33.255507 39.528023
|
||||
10.640629 37.713774 30.208056
|
||||
3.363033 36.409599 39.058745
|
||||
11.715459 45.522667 32.434962
|
||||
13.464532 47.534408 37.701884
|
||||
5.753267 33.153432 38.744854
|
||||
18.406300 45.310872 29.325427
|
||||
13.206913 40.476137 23.713366
|
||||
8.022162 30.669901 22.709029
|
||||
3.752878 32.705859 37.542413
|
||||
1.610955 47.782385 29.385167
|
||||
3.282363 49.872369 28.006430
|
||||
15.645580 31.838090 35.763354
|
||||
4.094538 33.332994 30.739124
|
||||
19.389613 49.000040 18.201493
|
||||
12.304495 31.002744 35.347648
|
||||
16.636205 41.587288 38.509899
|
||||
16.242905 37.908027 22.830238
|
||||
5.293874 39.810962 24.214172
|
||||
17.730042 40.807401 24.413293
|
||||
10.848526 46.719333 35.651427
|
||||
7.126381 30.842360 33.846795
|
||||
5.959882 33.494248 22.053307
|
||||
19.655118 37.249880 30.995999
|
||||
17.472236 42.954364 33.867949
|
||||
8.702629 44.307435 34.928355
|
||||
14.553503 36.391143 23.208353
|
||||
16.004125 47.562957 34.801544
|
||||
11.432695 47.088634 33.492738
|
||||
18.226320 43.756214 35.926311
|
||||
3.436149 42.651048 38.536654
|
||||
13.874327 30.831422 25.310616
|
||||
14.802646 40.372075 29.327322
|
||||
17.366240 48.310718 23.205411
|
||||
18.883354 33.973377 34.189039
|
||||
4.940024 38.820683 21.764487
|
||||
6.389472 34.087807 31.184860
|
||||
9.686298 46.746346 32.711941
|
||||
14.858616 49.173689 28.350539
|
||||
12.892325 33.920028 27.283556
|
||||
10.997502 36.579405 32.044916
|
||||
17.125470 47.650177 29.239499
|
||||
10.673225 33.505780 21.271442
|
||||
15.673616 33.342102 36.331892
|
||||
19.150955 35.558436 38.191118
|
||||
7.109812 49.243617 18.690492
|
||||
6.496059 31.449753 32.600549
|
||||
16.655108 39.629968 37.582826
|
||||
10.026644 39.787402 21.084604
|
||||
7.611422 40.274845 26.509155
|
||||
19.789113 39.105677 19.207532
|
||||
2.261065 37.897836 16.342341
|
||||
3.544031 45.823398 29.063016
|
||||
8.128766 31.176403 35.862979
|
||||
1.144189 43.284815 36.664338
|
||||
11.880560 36.253201 23.576926
|
||||
16.624167 49.768690 39.240587
|
||||
15.503963 36.766183 20.953801
|
||||
17.806003 30.839724 27.752022
|
||||
8.304373 48.787565 21.408915
|
||||
10.181775 35.977743 18.438917
|
||||
17.122472 34.268485 38.754985
|
||||
5.311906 43.788904 17.804844
|
||||
12.012478 31.562773 17.345468
|
||||
19.961598 36.302881 28.623923
|
||||
19.538837 36.303158 31.781007
|
||||
4.523682 48.587788 33.198009
|
||||
13.324998 42.192480 29.795723
|
||||
1.123948 43.299255 23.155238
|
||||
17.451114 45.355883 24.606045
|
||||
4.411658 44.468014 25.506241
|
||||
3.964021 38.375390 37.494247
|
||||
3.342860 44.301725 24.667203
|
||||
16.858232 33.418985 37.621960
|
||||
17.575051 42.057543 21.681617
|
||||
3.721699 44.550901 22.869235
|
||||
4.536435 32.653021 20.354643
|
||||
12.418668 47.807467 24.510958
|
||||
3.480837 37.949268 25.698086
|
||||
17.659928 48.015778 25.153195
|
||||
3.404855 39.565089 37.688459
|
||||
19.441124 45.664148 24.812879
|
||||
15.163402 48.596491 28.147741
|
||||
7.069610 34.859944 37.842481
|
||||
10.350486 40.456093 36.237884
|
||||
19.801801 40.683590 39.924546
|
||||
7.334750 39.747428 31.758286
|
||||
18.418554 30.115213 16.453879
|
||||
5.771517 49.221621 20.668848
|
||||
18.747257 49.783529 38.782999
|
||||
12.681107 36.749221 26.025580
|
||||
18.648049 31.794062 33.729165
|
||||
3.086854 38.310420 27.893166
|
||||
@@ -0,0 +1,6 @@
|
||||
5
|
||||
12.902894 37.503373 16.794572
|
||||
17.416074 36.974148 25.587149
|
||||
10.553441 48.572870 29.755519
|
||||
17.050082 30.582756 20.557365
|
||||
7.733536 30.049830 22.686053
|
||||
61
test/old_tests/inversion_2/fortran/ega5/input/STATIONS.txt
Normal file
61
test/old_tests/inversion_2/fortran/ega5/input/STATIONS.txt
Normal file
@@ -0,0 +1,61 @@
|
||||
60
|
||||
0.0 36.472809 29.812050
|
||||
0.0 42.546922 16.133799
|
||||
0.0 30.991032 23.169443
|
||||
0.0 46.965102 39.508986
|
||||
0.0 47.511915 37.527905
|
||||
0.0 48.435600 20.814328
|
||||
0.0 41.863499 15.672084
|
||||
0.0 32.635381 25.986810
|
||||
0.0 38.657687 39.966088
|
||||
0.0 40.746866 34.837968
|
||||
0.0 42.548883 27.938223
|
||||
0.0 45.654715 39.054882
|
||||
0.0 35.547420 37.107352
|
||||
0.0 34.000382 19.128119
|
||||
0.0 44.563868 35.283488
|
||||
0.0 40.983368 32.490992
|
||||
0.0 41.849069 38.852775
|
||||
0.0 30.415956 28.399387
|
||||
0.0 39.547377 26.435165
|
||||
0.0 32.064886 30.332071
|
||||
0.0 42.476838 23.230493
|
||||
0.0 34.956877 26.244838
|
||||
0.0 42.093400 15.092363
|
||||
0.0 37.363268 23.303628
|
||||
0.0 41.913218 33.323567
|
||||
0.0 43.569418 26.558183
|
||||
0.0 36.206968 29.037593
|
||||
0.0 30.241436 25.506620
|
||||
0.0 44.117881 30.429571
|
||||
0.0 39.517000 34.746538
|
||||
0.0 37.361734 22.829658
|
||||
0.0 49.421317 23.380557
|
||||
0.0 35.352432 34.053354
|
||||
0.0 42.126659 22.069541
|
||||
0.0 40.290506 34.457216
|
||||
0.0 37.633977 35.795705
|
||||
0.0 42.640993 22.595143
|
||||
0.0 41.972681 38.966854
|
||||
0.0 43.073835 35.660796
|
||||
0.0 45.484914 23.240725
|
||||
0.0 44.787236 30.506240
|
||||
0.0 36.156778 18.188633
|
||||
0.0 34.670427 29.724995
|
||||
0.0 48.621299 19.602209
|
||||
0.0 35.103483 16.672438
|
||||
0.0 48.315182 37.314071
|
||||
0.0 42.367526 34.248809
|
||||
0.0 39.728066 28.578711
|
||||
0.0 44.531207 26.103171
|
||||
0.0 31.457146 27.143870
|
||||
0.0 31.580000 17.230000
|
||||
0.0 32.120000 19.330000
|
||||
0.0 49.220000 16.330000
|
||||
0.0 45.630000 18.290000
|
||||
0.0 40.870000 19.970000
|
||||
0.0 48.740000 27.460000
|
||||
0.0 47.520000 32.420000
|
||||
0.0 33.250000 33.980000
|
||||
0.0 30.990000 34.470000
|
||||
0.0 31.120000 39.100000
|
||||
@@ -0,0 +1,6 @@
|
||||
5
|
||||
0.0 36.472809 29.812050
|
||||
0.0 42.546922 16.133799
|
||||
0.0 30.991032 23.169443
|
||||
0.0 46.965102 39.508986
|
||||
0.0 47.511915 37.527905
|
||||
@@ -0,0 +1,737 @@
|
||||
include "eikon_solver_mpi.f90"
|
||||
|
||||
|
||||
! example: 3-D 3rd order anisotropic eikonal equation in cartesian coordinate (Point source)
|
||||
! parameter setting:
|
||||
! domain: R * Theta * Phi = [6275, 6375] * [49^\circ, 51^\circ] * [129^\circ, 131^\circ]
|
||||
! analytic solution: T = |x-x_s|/c0
|
||||
! isotropic eik equ: Tx^2 + Ty^2 + Tz^2 = s^2,
|
||||
! boundary condition: T(x0,y0,z0) = 0 (point source)
|
||||
! test function: 'FSM_WENO3_PS_sphe_3d' in "eikon_solver.f90"
|
||||
!
|
||||
|
||||
program eikonal_2d
|
||||
use mpi
|
||||
|
||||
! ######################### 参数声明 parameters statement #########################
|
||||
|
||||
implicit none
|
||||
|
||||
! mesh grid
|
||||
integer,parameter :: nr=55,nt=55,np=55
|
||||
double precision,parameter :: pi=3.14159265358979323846264338327950288
|
||||
double precision,parameter :: rr1=6070,rr2=6400
|
||||
double precision,parameter :: tt1=(30.0-1.5)/180*pi,tt2=(50.0+1.5)/180*pi
|
||||
double precision,parameter :: pp1=(15.0-1.5)/180*pi,pp2=(40.0+1.5)/180*pi
|
||||
double precision :: rr(nr),tt(nt),pp(np),dr,dt,dp
|
||||
|
||||
|
||||
! source (STATIONS) & receiver (EARTHQUAKES)
|
||||
integer :: nsou
|
||||
double precision,allocatable :: rsou(:),tsou(:),psou(:) ! source (station)
|
||||
integer :: nrec
|
||||
double precision,allocatable :: rrec(:),trec(:),prec(:) ! receiver (earthquake)
|
||||
|
||||
! model parameter
|
||||
double precision,parameter :: gamma = 0.0
|
||||
double precision :: xi(nr,nt,np),eta(nr,nt,np),zeta(nr,nt,np) ! syn model (ani)
|
||||
double precision :: xiT(nr,nt,np),etaT(nr,nt,np),zetaT(nr,nt,np) ! true model (ani)
|
||||
double precision :: sigma1,sigma2,psi
|
||||
double precision,parameter :: slow_p=0.04,ani_p=0.03
|
||||
|
||||
! Eikonal solver
|
||||
double precision :: aT(nr,nt,np),bT(nr,nt,np),cT(nr,nt,np),fT(nr,nt,np),funT(nr,nt,np) ! true model 真实模型
|
||||
double precision :: a(nr,nt,np),b(nr,nt,np),c(nr,nt,np),f(nr,nt,np),fun(nr,nt,np) ! syn model 猜测模型
|
||||
double precision :: uT(nr,nt,np),TableT(nr,nt,np) !true timetable 真实走时场
|
||||
double precision :: u(nr,nt,np),Table(nr,nt,np) !syn timetable 猜测走时场
|
||||
!double precision :: T0para(8),tau(nr,nt,np) ! multiplicative factor
|
||||
|
||||
! adjoint source
|
||||
double precision,allocatable :: sourceADJ(:),TtimeT(:,:),Ttime(:,:) ! adjoint source 伴随源,真实走时，合成走时
|
||||
double precision :: TableADJ(nr,nt,np) ! adjoint field 伴随场
|
||||
double precision :: Ks(nr,nt,np),Kxi(nr,nt,np),Keta(nr,nt,np) ! event kernel
|
||||
integer,parameter :: nk = 3 ! number of kernels
|
||||
double precision :: all_Ks(nr,nt,np),all_Kxi(nr,nt,np),all_Keta(nr,nt,np) ! sensitivity kernel
|
||||
double precision :: all_Kernel(nr,nt,np,nk) ! kernels for all parameters together
|
||||
!double precision,parameter :: radius = 40 ! kernel mask radius
|
||||
|
||||
! inversion grid
|
||||
integer,parameter :: ninvr=11,ninvt=10,ninvp=10 ! inversion grid size (coarse)
|
||||
double precision,parameter :: invr1=6070.0,invr2=6400.0
|
||||
double precision,parameter :: invt1=30.0/180*pi,invt2=50.0/180*pi
|
||||
double precision,parameter :: invp1=15.0/180*pi,invp2=40.0/180*pi
|
||||
integer,parameter :: ngrid=5 ! number of nultigrid (multigrid technique)
|
||||
double precision :: invr(ngrid,ninvr),invt(ngrid,ninvt),invp(ngrid,ninvp),dinvr,dinvt,dinvp
|
||||
double precision :: update_value(nr,nt,np,nk) ! parameter update value 更新参数的变化量
|
||||
|
||||
! model update (optimization)
|
||||
double precision :: stepsize ! stepsize
|
||||
integer,parameter :: MaxIter=1 ! max iteration step
|
||||
double precision :: old_obj, obj, sou_obj ! 优化目标函数 objective function
|
||||
double precision,allocatable :: weight_sou(:),weight_rec(:) !weight function
|
||||
double precision :: dis_ij, dis_zero !weight function
|
||||
logical :: weight_sou_bool=.false. , weight_rec_bool= .false.
|
||||
|
||||
! temp var
|
||||
double precision :: depth,lat,lon
|
||||
|
||||
! output file
|
||||
character(Len=80) :: filename,form,form2
|
||||
|
||||
! loop index
|
||||
integer :: iir,iit,iip,idi,idj,idk,i,j,k,iter,igrid
|
||||
|
||||
! computing time
|
||||
double precision :: time_begin,time_end,alpha
|
||||
|
||||
! mpi parameter
|
||||
integer :: ierr,myid,nproc
|
||||
|
||||
! ############################# main work #############################
|
||||
|
||||
call mpi_init(ierr)
|
||||
|
||||
call mpi_comm_rank(mpi_comm_world,myid,ierr)
|
||||
call mpi_comm_size(mpi_comm_world,nproc,ierr)
|
||||
|
||||
call CPU_TIME(time_begin) ! program start
|
||||
|
||||
|
||||
|
||||
! ################### read sources and receivers 读取地震台站数据 ###################
|
||||
open(10,file='ega5/input/STATIONS_5.txt')
|
||||
read(10,*) nsou
|
||||
allocate(rsou(nsou),tsou(nsou),psou(nsou),weight_sou(nsou))
|
||||
do i=1,nsou
|
||||
read(10,*) depth,lat,lon
|
||||
rsou(i) = 6371.0-depth
|
||||
tsou(i) = lat/180.0*pi
|
||||
psou(i) = lon/180.0*pi
|
||||
end do
|
||||
close(10)
|
||||
|
||||
open(10,file='ega5/input/EARTHQUAKES_5.txt')
|
||||
read(10,*) nrec
|
||||
allocate(rrec(nrec),trec(nrec),prec(nrec),weight_rec(nrec))
|
||||
do i=1,nrec
|
||||
read(10,*) depth,lat,lon
|
||||
rrec(i) = 6371.0-depth
|
||||
trec(i) = lat/180.0*pi
|
||||
prec(i) = lon/180.0*pi
|
||||
end do
|
||||
close(10)
|
||||
|
||||
! distance based weight -rec 台站权重
|
||||
if (weight_rec_bool) then
|
||||
dis_zero = 0
|
||||
do i=1,nrec-1
|
||||
do j=i,nrec
|
||||
call Epicenter_Distance(trec(i),prec(i),trec(j),prec(j),dis_ij)
|
||||
dis_zero = dis_zero + dis_ij
|
||||
end do
|
||||
end do
|
||||
dis_zero = dis_zero/nrec/(nrec-1)*2
|
||||
dis_zero = dis_zero/2
|
||||
|
||||
do i=1,nrec
|
||||
weight_rec(i)=0.0
|
||||
do j=1,nrec
|
||||
call Epicenter_Distance(trec(i),prec(i),trec(j),prec(j),dis_ij)
|
||||
weight_rec(i) = weight_rec(i) + exp(-(dis_ij/dis_zero)**2)
|
||||
end do
|
||||
weight_rec(i) = 1.0/weight_rec(i)
|
||||
end do
|
||||
print *, dis_zero
|
||||
end if
|
||||
|
||||
if (weight_rec_bool) then
|
||||
! distance based weight - soruce 地震权重
|
||||
dis_zero = 0
|
||||
do i=1,nsou-1
|
||||
do j=i,nsou
|
||||
call Epicenter_Distance(tsou(i),psou(i),tsou(j),psou(j),dis_ij)
|
||||
dis_zero = dis_zero + dis_ij
|
||||
end do
|
||||
end do
|
||||
dis_zero = dis_zero/nsou/(nsou-1)*2
|
||||
dis_zero = dis_zero/4
|
||||
|
||||
do i=1,nsou
|
||||
weight_sou(i)=0.0
|
||||
do j=1,nsou
|
||||
call Epicenter_Distance(tsou(i),psou(i),tsou(j),psou(j),dis_ij)
|
||||
weight_sou(i) = weight_sou(i) + exp(-(dis_ij/dis_zero)**2)
|
||||
end do
|
||||
weight_sou(i) = 1.0/weight_sou(i)
|
||||
end do
|
||||
print *, dis_zero
|
||||
end if
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (myid .eq. 0) then
|
||||
open(100,file='ega5/output/STATIONS')
|
||||
open(101,file='ega5/output/EARTHQUAKES')
|
||||
do i=1,nsou
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7)') rsou(i),tsou(i),psou(i),weight_sou(i)
|
||||
end do
|
||||
do i=1,nrec
|
||||
write(101,'(f13.7,f13.7,f13.7,f13.7)') rrec(i),trec(i),prec(i),weight_rec(i)
|
||||
end do
|
||||
close(100);close(101)
|
||||
end if
|
||||
|
||||
! ######################### 生成网格 build mesh grid #####################################
|
||||
! -------- forward modeling grid ----------
|
||||
dr=(rr2-rr1)/(nr-1); dt=(tt2-tt1)/(nt-1); dp=(pp2-pp1)/(np-1)
|
||||
do iir=1,nr
|
||||
rr(iir)=rr1+(iir-1)*dr
|
||||
end do
|
||||
do iit=1,nt
|
||||
tt(iit)=tt1+(iit-1)*dt
|
||||
end do
|
||||
do iip=1,np
|
||||
pp(iip)=pp1+(iip-1)*dp
|
||||
end do
|
||||
|
||||
! -------- inversion multigrid ----------
|
||||
dinvr=(invr2-invr1)/(ninvr-1); dinvt=(invt2-invt1)/(ninvt-1); dinvp=(invp2-invp1)/(ninvp-1)
|
||||
do igrid=1,ngrid
|
||||
do iir=1,ninvr
|
||||
invr(igrid,iir)=invr1+(iir-1)*dinvr-(igrid-1)*dinvr/ngrid
|
||||
end do
|
||||
do iit=1,ninvt
|
||||
invt(igrid,iit)=invt1+(iit-1)*dinvt-(igrid-1)*dinvt/ngrid
|
||||
end do
|
||||
do iip=1,ninvp
|
||||
invp(igrid,iip)=invp1+(iip-1)*dinvp-(igrid-1)*dinvp/ngrid
|
||||
end do
|
||||
end do
|
||||
|
||||
! ######################### 构建背景模型 build the synthetic and true model #####################################
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
|
||||
! synthetic (initial) model
|
||||
eta(iir,iit,iip)=0.0;
|
||||
xi(iir,iit,iip)=0.0;
|
||||
zeta(iir,iit,iip)=gamma*sqrt(eta(iir,iit,iip)**2+xi(iir,iit,iip)**2)
|
||||
! if (rr(iir)>6351) then ! 6371 - 6351 20 km
|
||||
! fun(iir,iit,iip) = 1.0/(5.8+(6371-rr(iir))/20.0*0.7)
|
||||
! elseif (rr(iir)>6336) then ! 6351 - 6336 15 km
|
||||
! fun(iir,iit,iip) = 1.0/(6.5+(6351-rr(iir))/15.0*0.6)
|
||||
! elseif (rr(iir)>6251) then ! 6336 - 6251 85 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.04+(6336-rr(iir))/85.0*0.01)
|
||||
! elseif (rr(iir)>6161) then ! 6251 - 6161 90 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.05+(6251-rr(iir))/90.0*0.25)
|
||||
! elseif (rr(iir)>5961) then ! 6161 - 5961 200 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.30+(6161-rr(iir))/200.0*0.73)
|
||||
! else
|
||||
! fun(iir,iit,iip) = 1.0/9.03
|
||||
! end if
|
||||
|
||||
if (rr(iir)>6351) then ! 6371 - 6351 20 km
|
||||
fun(iir,iit,iip) = 1.0/(5.8+(6371-rr(iir))/20.0*0.7)
|
||||
elseif (rr(iir)>6336) then ! 6351 - 6336 15 km
|
||||
fun(iir,iit,iip) = 1.0/(6.5+(6351-rr(iir))/15.0*0.6)
|
||||
elseif (rr(iir)>5961) then ! 6351 - 6336 15 km
|
||||
fun(iir,iit,iip) = 1.0/(8.0+(6336-rr(iir))/375.0*1)
|
||||
else
|
||||
fun(iir,iit,iip) = 1.0/9.0
|
||||
end if
|
||||
|
||||
|
||||
!read(100,*) xi(iir,iit,iip)
|
||||
!read(101,*) eta(iir,iit,iip)
|
||||
!read(102,*) fun(iir,iit,iip)
|
||||
|
||||
a(iir,iit,iip)=1.0+2*zeta(iir,iit,iip);
|
||||
b(iir,iit,iip)=1.0-2*xi(iir,iit,iip);
|
||||
c(iir,iit,iip)=1.0+2*xi(iir,iit,iip);
|
||||
f(iir,iit,iip)=-2*eta(iir,iit,iip);
|
||||
|
||||
Table(iir,iit,iip) = 0
|
||||
|
||||
|
||||
|
||||
! true (target) model
|
||||
if (tt(iit)>=30.0/180*pi .and. tt(iit)<=50.0/180*pi .and. &
|
||||
& pp(iip)>=15.0/180*pi .and. pp(iip)<=40.0/180*pi .and. &
|
||||
& rr(iir)>=6211.0 .and. rr(iir)<=6371.0 ) then
|
||||
sigma1 = sin(4*pi*(tt(iit)-30.0/180*pi)/(20.0/180*pi))* &
|
||||
& sin(4*pi*(pp(iip)-15.0/180*pi)/(25.0/180*pi))* &
|
||||
& sin(2*pi*(rr(iir)-6211)/160.0)
|
||||
else
|
||||
sigma1 = 0.0
|
||||
end if
|
||||
|
||||
|
||||
if (sigma1<0) then
|
||||
psi = 60.0/180*pi
|
||||
elseif (sigma1 > 0) then
|
||||
psi = 150.0/180*pi
|
||||
else
|
||||
psi = 0
|
||||
end if
|
||||
|
||||
etaT(iir,iit,iip)=ani_p*abs(sigma1)*sin(2*psi);
|
||||
xiT(iir,iit,iip)=ani_p*abs(sigma1)*cos(2*psi);
|
||||
zetaT(iir,iit,iip)=gamma*sqrt(etaT(iir,iit,iip)**2+xiT(iir,iit,iip)**2)
|
||||
|
||||
aT(iir,iit,iip)=1.0+2*zetaT(iir,iit,iip);
|
||||
bT(iir,iit,iip)=1.0-2*xiT(iir,iit,iip);
|
||||
cT(iir,iit,iip)=1.0+2*xiT(iir,iit,iip);
|
||||
fT(iir,iit,iip)=-2*etaT(iir,iit,iip);
|
||||
funT(iir,iit,iip) = fun(iir,iit,iip)/(1+sigma1*slow_p)
|
||||
|
||||
!fun(iir,iit,iip) = funT(iir,iit,iip)
|
||||
!eta(iir,iit,iip)=etaT(iir,iit,iip);
|
||||
!xi(iir,iit,iip)=xiT(iir,iit,iip);
|
||||
!zeta(iir,iit,iip)=zetaT(iir,iit,iip)
|
||||
!a(iir,iit,iip)=aT(iir,iit,iip)
|
||||
!b(iir,iit,iip)=bT(iir,iit,iip)
|
||||
!c(iir,iit,iip)=cT(iir,iit,iip)
|
||||
!f(iir,iit,iip)=fT(iir,iit,iip)
|
||||
|
||||
TableT(iir,iit,iip) = 0
|
||||
u(iir,iit,iip) = 0
|
||||
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (myid==0) then
|
||||
open(100,file='ega5/output/model_true')
|
||||
open(101,file='ega5/output/model_init')
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& funT(iir,iit,iip),xiT(iir,iit,iip),etaT(iir,iit,iip)
|
||||
write(101,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& fun(iir,iit,iip),xi(iir,iit,iip),eta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100);close(101)
|
||||
|
||||
! --------- 多重网格 multiple grid ------
|
||||
do igrid=1,Ngrid
|
||||
select case(igrid)
|
||||
case (1:9)
|
||||
write(form,'(I1)') igrid
|
||||
case (10:99)
|
||||
write(form,'(I2)') igrid
|
||||
end select
|
||||
open(100,file='ega5/output/multigrid'//trim(form))
|
||||
|
||||
do iir=1,ninvr
|
||||
do iit=1,ninvt
|
||||
do iip=1,ninvp
|
||||
write(100,'(f13.7,f13.7,f13.7)') &
|
||||
& invr(igrid,iir),invt(igrid,iit),invp(igrid,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end do
|
||||
|
||||
end if
|
||||
|
||||
|
||||
! ######################### 计算真实到时 calculate true traveltimes ######################
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
allocate(TtimeT(nsou,nrec)) ! 初始化真实到时表 initiate true traveltimes
|
||||
allocate(Ttime(nsou,nrec)) ! 初始化合成到时表 initiate syn traveltimes
|
||||
allocate(sourceADJ(nrec)) ! 初始化伴随源 initiate adjoint source
|
||||
|
||||
if (myid==0) then
|
||||
print *, ' '
|
||||
print *, '----------------- calculating true timetable ... ----------------'
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
do i=1,nsou ! loop sources (STATIONS)
|
||||
! -------- 求解程函方程 solve eikonal equations ------------
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
!rsou(i)=6371.0; tsou(i)=30.5/180.0*pi; psou(i)=15.5/180.0*pi
|
||||
call FSM_WENO3_PS_sphe_3d_mul_mpi(rr,tt,pp,nr,nt,np,aT,bT,cT,fT,TableT,funT,rsou(i),tsou(i),psou(i),u)
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
! -------- 得到真实走时 calculate true arrival time at receiver --------
|
||||
call Linear_Interp_3D(rr,tt,pp,TableT,nr,nt,np,rrec,trec,prec,TtimeT(i,:),nrec)
|
||||
!if ((myid.eq.0) .and. 1>0) then
|
||||
! print *, rsou(i),tsou(i)/pi*180,psou(i)/pi*180
|
||||
! open(100,file='ega5/output/arrivaltime')
|
||||
! do j=1,nrec
|
||||
! write(100,'(i5.3,f8.2,f6.2,f6.2,f8.3)') j, rrec(j),trec(j)/pi*180,prec(j)/pi*180,TtimeT(i,j)
|
||||
! end do
|
||||
! close(100)
|
||||
!end if
|
||||
end do
|
||||
|
||||
print *, '----------------- calculating true timetable over ---------------- '
|
||||
|
||||
! ######################## 反演开始 inversion start ##########################
|
||||
|
||||
! ----- 初始化反演参数 initiate inversion parameters ----
|
||||
stepsize = 0.01 ! 迭代步长 stepsize
|
||||
old_obj = 0; obj = 0 ! 目标函数 objective function
|
||||
|
||||
|
||||
|
||||
if (myid .eq. 0) then
|
||||
print *, ' '
|
||||
print *, '----------------- inversion start ... ----------------'
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
|
||||
|
||||
do iter = 1,MaxIter
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
if (myid .eq. 0) then
|
||||
print *, '----------------- iteration ',iter,' starting ... ----------------'
|
||||
end if
|
||||
|
||||
! ----- 初始化参数 initiate parameters ------
|
||||
all_Ks = 0; all_Kxi = 0; all_Keta = 0;
|
||||
obj = 0;
|
||||
|
||||
if (myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/misfit_step'//trim(form)
|
||||
open(998, file=trim(filename))
|
||||
end if
|
||||
|
||||
|
||||
do i=1,nsou ! loop sources (STATIONS)
|
||||
|
||||
! ######################## 计算合成走时场 calculate synthetic timetable ########################
|
||||
if (myid .eq. 0) then
|
||||
print *, '----------------- calculating synthetic timetable ... ----------------'
|
||||
end if
|
||||
|
||||
Table = 20
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
call FSM_WENO3_PS_sphe_3d_mul_mpi(rr,tt,pp,nr,nt,np,a,b,c,f,Table,fun,rsou(i),tsou(i),psou(i),u)
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
! -------- 得到合成走时 calculate synthetic arrival time at receiver --------
|
||||
call Linear_Interp_3D(rr,tt,pp,Table,nr,nt,np,rrec,trec,prec,Ttime(i,:),nrec)
|
||||
|
||||
! -------- 构造伴随源 build adjoint source -------
|
||||
call Adjoint_Source_Dt(Ttime(i,:),TtimeT(i,:),nrec,sourceADJ,sou_obj) ! absolute traveltime difference
|
||||
if (myid .eq. 0) then
|
||||
do j=1,nrec
|
||||
write(998,'(f10.5)') Ttime(i,j)-TtimeT(i,j)
|
||||
end do
|
||||
end if
|
||||
|
||||
! weighting adjoint source
|
||||
if (weight_rec_bool) then
|
||||
do j=1,nrec
|
||||
sourceADJ(j) = sourceADJ(j) * weight_rec(j)
|
||||
end do
|
||||
end if
|
||||
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/syn_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7)') Table(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
!
|
||||
|
||||
!print *, Ttime(i,:),TtimeT(i,:)
|
||||
!call Adjoint_Source_Ddt(Ttime(i,:),TtimeT(i,:),nrec,sourceADJ,sou_obj) ! double difference traveltime
|
||||
!do j=1,nrec-1
|
||||
! do k=j,nrec
|
||||
! write(998,'(f10.5)') (Ttime(i,j)-Ttime(i,k))-(TtimeT(i,j)-TtimeT(i,k))
|
||||
! end do
|
||||
!end do
|
||||
|
||||
! ######################## 计算伴随场 adjoint field ########################
|
||||
if (myid .eq. 0) then
|
||||
! print *, '----------------- calculating adjoint field ... ----------------'
|
||||
end if
|
||||
call FSM_O1_Adj_sphe_3d(rr,tt,pp,nr,nt,np,Table,TableADJ,zeta,xi,eta,nrec,rrec,trec,prec,sourceADJ)
|
||||
!call FSM_O1_Adj_PS_sphe_3d(rr,tt,pp,nr,nt,np,T0para,tau,TableADJ,zeta,xi,eta,nrec,rrec,trec,prec,sourceADJ)
|
||||
! ---- 记录到 matlab 数据中 matlab record (adjoint field) ----
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/adj_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7)') TableADJ(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
! ######################## 计算敏感核 sensitivity kernel ########################
|
||||
!print *, '----------------- calculating kernel ... ----------------'
|
||||
call Sensitivity_Kernel(rr,tt,pp,nr,nt,np,Table,TableADJ,gamma,xi,eta,fun,Ks,Kxi,Keta)
|
||||
|
||||
! ------- 抹去伴随源处的大函数值 mask the source -------
|
||||
!print *, '----------------- kernel mask ----------------'
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Ks,rsou(i),tsou(i),psou(i),radius)
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Kxi,rsou(i),tsou(i),psou(i),radius)
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Keta,rsou(i),tsou(i),psou(i),radius)
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Ks,rsou(i),tsou(i),psou(i))
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Kxi,rsou(i),tsou(i),psou(i))
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Keta,rsou(i),tsou(i),psou(i))
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record (adjoint field) ----
|
||||
if (1<0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/kernel_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& Ks(iir,iit,iip),Kxi(iir,iit,iip),Keta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
! --------- 敏感核,obj叠加 sum kernels and objective function -------
|
||||
if (weight_sou_bool) then ! no weight
|
||||
all_Ks = all_Ks + Ks * weight_sou(i);
|
||||
all_Kxi = all_Kxi + Kxi * weight_sou(i);
|
||||
all_Keta = all_Keta + Keta * weight_sou(i);
|
||||
obj = obj + sou_obj !* weight_sou(i)
|
||||
else ! source weighted
|
||||
all_Ks = all_Ks + Ks;
|
||||
all_Kxi = all_Kxi + Kxi;
|
||||
all_Keta = all_Keta + Keta;
|
||||
obj = obj + sou_obj
|
||||
end if
|
||||
|
||||
end do
|
||||
|
||||
close(998)
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record (kernel) ----
|
||||
if (1>0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/kernel_step'//trim(form)//'_sum'
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& all_Ks(iir,iit,iip),all_Kxi(iir,iit,iip),all_Keta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
! ##################### 模型更新 model update ####################
|
||||
print *, '----------------- model updating ... ----------------'
|
||||
|
||||
all_Kernel(:,:,:,1) = all_Ks;
|
||||
all_Kernel(:,:,:,2) = all_Kxi;
|
||||
all_Kernel(:,:,:,3) = all_Keta;
|
||||
|
||||
! ------------ 更新速度(慢度) update velocity (slowness) ------------
|
||||
call Parameter_Update_Multigrid(rr,tt,pp,nr,nt,np,all_Kernel,nk, &
|
||||
& invr,invt,invp,ninvr,ninvt,ninvp,ngrid,stepsize,update_value)
|
||||
|
||||
if (1<0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/model_update_step'//trim(form)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& -fun(iir,iit,iip)*update_value(iir,iit,iip,1), &
|
||||
& -update_value(iir,iit,iip,2),-update_value(iir,iit,iip,3)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
fun(iir,iit,iip) = fun(iir,iit,iip)*(1-update_value(iir,iit,iip,1))
|
||||
!fun(iir,iit,iip) = fun(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ------------ 更新xi update xi ------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
xi(iir,iit,iip) = xi(iir,iit,iip)-update_value(iir,iit,iip,2)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ------------ 更新eta update eta ------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
eta(iir,iit,iip) = eta(iir,iit,iip)-update_value(iir,iit,iip,3)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ----------- 更新 update eikonal solver paramater -----------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
b(iir,iit,iip)=1.0-2*xi(iir,iit,iip);
|
||||
c(iir,iit,iip)=1.0+2*xi(iir,iit,iip);
|
||||
f(iir,iit,iip)=-2*eta(iir,iit,iip);
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
|
||||
|
||||
|
||||
! ##################### 调整下降步长 modify stepsize #############
|
||||
if (myid .eq. 0) then
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
open(999,file='ega5/output/obj',access='append')
|
||||
write(999,'(f9.2,f9.6)') obj, stepsize
|
||||
close(999)
|
||||
end if
|
||||
|
||||
if (iter == 1 ) then
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2)') 'iter 1, obj is', obj
|
||||
write(*,'(a,f9.6)') 'iter 1, stepsize is', stepsize
|
||||
end if
|
||||
elseif (iter >= 2 .and. obj < old_obj) then
|
||||
!stepsize = min(0.01,stepsize*1.2)
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2,a,f9.2)') 'objective function decreases, from', old_obj, ' to', obj
|
||||
write(*,'(a,f9.6)') 'new stepsize is ', stepsize
|
||||
end if
|
||||
elseif (iter >= 2 .and. obj >= old_obj) then
|
||||
!stepsize = max(0.002,stepsize*0.5)
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2,a,f9.2)') 'objective function increases, from', old_obj, ' to', obj
|
||||
write(*,'(a,f9.6)') 'new stepsize is ', stepsize
|
||||
end if
|
||||
end if
|
||||
|
||||
print *, '----------------- iteration ',iter,' over ----------------'
|
||||
print *, ' '
|
||||
print *, ' '
|
||||
|
||||
|
||||
old_obj = obj
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/model_step'//trim(form)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& fun(iir,iit,iip),xi(iir,iit,iip),eta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
|
||||
if (myid .eq. 0) then
|
||||
call CPU_TIME(time_end)
|
||||
write(*,'(f10.2)') time_end - time_begin
|
||||
end if
|
||||
|
||||
end do
|
||||
|
||||
|
||||
call mpi_finalize(ierr)
|
||||
|
||||
end program eikonal_2d
|
||||
|
||||
2836
test/old_tests/inversion_2/fortran/eikon_solver_mpi.f90
Normal file
2836
test/old_tests/inversion_2/fortran/eikon_solver_mpi.f90
Normal file
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
54
test/old_tests/inversion_2/input_params.yml
Normal file
54
test/old_tests/inversion_2/input_params.yml
Normal file
@@ -0,0 +1,54 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0,301.0] # depth in km
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
#src_rec_file : 'src_rec_compare_with_fortran_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
optim_method : 2 # optimization method. 0 : "grad_descent", 1 : "lbfgs", 2 : "halve-stepping"
|
||||
smooth_method : 0 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
max_iterations_inv : 100 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
|
||||
# parameters for multiparametric inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [11,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [30.0,50.0] # latitude in degree
|
||||
min_max_lon_inv : [15.0,40.0] # longitude in degree
|
||||
# parameters for laplacian smoothing
|
||||
l_smooth_rtp : [1,1,1] # smoothing coefficients for each direction
|
||||
regularization_weight : 2000.0 # regularization weight
|
||||
# parameter for halving-stepping or lbfgs
|
||||
max_sub_iterations : 100 # maximum number of sub-iterations
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [2,2,2] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
use_gpu : 0
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
36
test/old_tests/inversion_2/input_params_pre.yml
Normal file
36
test/old_tests/inversion_2/input_params_pre.yml
Normal file
@@ -0,0 +1,36 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0,301.0] # depth in km
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
#src_rec_file : 'src_rec_compare_with_fortran.txt' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,1,1] # number of subdomains
|
||||
nproc_sub : 8 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
328
test/old_tests/inversion_2/make_test_model.ipynb
Normal file
328
test/old_tests/inversion_2/make_test_model.ipynb
Normal file
@@ -0,0 +1,328 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"#R_earth = 6378.1370\n",
|
||||
"R_earth = 6371.0\n",
|
||||
"\n",
|
||||
"rr1=6070\n",
|
||||
"rr2=6400\n",
|
||||
"tt1=(30.0-1.5)/180*math.pi\n",
|
||||
"tt2=(50.0+1.5)/180*math.pi\n",
|
||||
"pp1=(15.0-1.5)/180*math.pi\n",
|
||||
"pp2=(40.0+1.5)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [55,55,55]\n",
|
||||
"n_rtp.reverse()\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[2]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[0]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"s0 = 1.0/6.0\n",
|
||||
"slow_p=0.04\n",
|
||||
"ani_p=0.03\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"a_init = np.zeros(n_rtp)\n",
|
||||
"b_init = np.zeros(n_rtp)\n",
|
||||
"c_init = np.zeros(n_rtp)\n",
|
||||
"f_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"a_true = np.zeros(n_rtp)\n",
|
||||
"b_true = np.zeros(n_rtp)\n",
|
||||
"c_true = np.zeros(n_rtp)\n",
|
||||
"f_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ip,it,ir] = 0.0\n",
|
||||
" #xi_init[ip,it,ir] = 0.0\n",
|
||||
" zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)\n",
|
||||
" \n",
|
||||
" if (rr[ir]>6351):\n",
|
||||
" fun_init[ip,it,ir] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)\n",
|
||||
" elif (rr[ir]>6336):\n",
|
||||
" fun_init[ip,it,ir] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)\n",
|
||||
" elif (rr[ir]>5961):\n",
|
||||
" fun_init[ip,it,ir] = 1.0/(8.0+(6336-rr[ir])/375.0*1) \n",
|
||||
" else:\n",
|
||||
" fun_init[ip,it,ir] = 1.0/9.0\n",
|
||||
"\n",
|
||||
" vel_init[ip,it,ir] = 1.0/fun_init[ip,it,ir]\n",
|
||||
" a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]\n",
|
||||
" b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]\n",
|
||||
" c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]\n",
|
||||
" f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \\\n",
|
||||
" and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 150.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)\n",
|
||||
" fun_true[ip,it,ir] = fun_init[ip,it,ir]/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir] \n",
|
||||
" a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]\n",
|
||||
" b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]\n",
|
||||
" c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]\n",
|
||||
" f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"print(\"depminmax {} {}\".format(R_earth-rr1,R_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init.T)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init.T)\n",
|
||||
"fout_init.create_dataset('zeta', data=zeta_init.T)\n",
|
||||
"fout_init.create_dataset('fun', data=fun_init.T)\n",
|
||||
"fout_init.create_dataset('fac_a', data=a_init.T)\n",
|
||||
"fout_init.create_dataset('fac_b', data=b_init.T)\n",
|
||||
"fout_init.create_dataset('fac_c', data=c_init.T)\n",
|
||||
"fout_init.create_dataset('fac_f', data=f_init.T)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init.T)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true.T)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true.T)\n",
|
||||
"fout_true.create_dataset('zeta', data=zeta_true.T)\n",
|
||||
"fout_true.create_dataset('fun', data=fun_true.T)\n",
|
||||
"fout_true.create_dataset('fac_a', data=a_true.T)\n",
|
||||
"fout_true.create_dataset('fac_b', data=b_true.T)\n",
|
||||
"fout_true.create_dataset('fac_c', data=c_true.T)\n",
|
||||
"fout_true.create_dataset('fac_f', data=f_true.T)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true.T)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(1145141919810)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 500\n",
|
||||
"n_rec = [60 for x in range(n_src)]\n",
|
||||
"#n_src = 10\n",
|
||||
"#n_rec = [10 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"# create receiver coordinates\n",
|
||||
"elev_recs=[]\n",
|
||||
"lon_recs=[]\n",
|
||||
"lat_recs=[]\n",
|
||||
"rec_names=[]\n",
|
||||
"for i in range(n_rec[0]):\n",
|
||||
" #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
|
||||
" elev_recs.append(0) # elevation in m\n",
|
||||
" lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
|
||||
" lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
|
||||
" rec_names.append(i)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" dep = random.uniform((R_earth-rr1)*0.1,(R_earth-rr1)*0.9)\n",
|
||||
" lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
" lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
" elev_rec = elev_recs[i_rec]\n",
|
||||
" lon_rec = lon_recs[i_rec]\n",
|
||||
" lat_rec = lat_recs[i_rec]\n",
|
||||
" st_name_dummy = rec_names[i_rec]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_rec,lat_rec,elev_rec])\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
14
test/old_tests/inversion_2_one_src/README.md
Normal file
14
test/old_tests/inversion_2_one_src/README.md
Normal file
@@ -0,0 +1,14 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` for creating
|
||||
- source, receiver file
|
||||
- true model
|
||||
- initial model
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
-> this will output src_rec_result.dat file which includes the arrival time at each station
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`.
|
||||
|
||||
64
test/old_tests/inversion_2_one_src/check_obj_func.ipynb
Normal file
64
test/old_tests/inversion_2_one_src/check_obj_func.ipynb
Normal file
@@ -0,0 +1,64 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# check the change of objective values\n",
|
||||
"\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"fpath='objective_function.txt'\n",
|
||||
"\n",
|
||||
"objs=[]\n",
|
||||
"\n",
|
||||
"with open(fpath) as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" for l in lines:\n",
|
||||
" if(l.startswith('i_inv')):\n",
|
||||
" continue\n",
|
||||
" objs.append(float(l.strip().split(',')[1]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"plt.plot(objs)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.4 (tags/v3.10.4:9d38120, Mar 23 2022, 23:13:41) [MSC v.1929 64 bit (AMD64)]"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "cdd74c396a461f81d13d16403c726c38089d3c42a4b6e59262cdb9511d16556b"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,3 @@
|
||||
mpif90 ega5_sphe_3d_inversion_Tong_3Dinv.f90 -o a5.out
|
||||
|
||||
mpirun -n 4 a5.out
|
||||
@@ -0,0 +1,2 @@
|
||||
1
|
||||
12.902894 37.503373 16.794572
|
||||
@@ -0,0 +1,2 @@
|
||||
1
|
||||
0.0 36.472809 29.812050
|
||||
@@ -0,0 +1,737 @@
|
||||
include "eikon_solver_mpi.f90"
|
||||
|
||||
|
||||
! example: 3-D 3rd order anisotropic eikonal equation in cartesian coordinate (Point source)
|
||||
! parameter setting:
|
||||
! domain: R * Theta * Phi = [6275, 6375] * [49^\circ, 51^\circ] * [129^\circ, 131^\circ]
|
||||
! analytic solution: T = |x-x_s|/c0
|
||||
! isotropic eik equ: Tx^2 + Ty^2 + Tz^2 = s^2,
|
||||
! boundary condition: T(x0,y0,z0) = 0 (point source)
|
||||
! test function: 'FSM_WENO3_PS_sphe_3d' in "eikon_solver.f90"
|
||||
!
|
||||
|
||||
program eikonal_2d
|
||||
use mpi
|
||||
|
||||
! ######################### 参数声明 parameters statement #########################
|
||||
|
||||
implicit none
|
||||
|
||||
! mesh grid
|
||||
integer,parameter :: nr=55,nt=55,np=55
|
||||
double precision,parameter :: pi=3.14159265358979323846264338327950288
|
||||
double precision,parameter :: rr1=6070,rr2=6400
|
||||
double precision,parameter :: tt1=(30.0-1.5)/180*pi,tt2=(50.0+1.5)/180*pi
|
||||
double precision,parameter :: pp1=(15.0-1.5)/180*pi,pp2=(40.0+1.5)/180*pi
|
||||
double precision :: rr(nr),tt(nt),pp(np),dr,dt,dp
|
||||
|
||||
|
||||
! source (STATIONS) & receiver (EARTHQUAKES)
|
||||
integer :: nsou
|
||||
double precision,allocatable :: rsou(:),tsou(:),psou(:) ! source (station)
|
||||
integer :: nrec
|
||||
double precision,allocatable :: rrec(:),trec(:),prec(:) ! receiver (earthquake)
|
||||
|
||||
! model parameter
|
||||
double precision,parameter :: gamma = 0.0
|
||||
double precision :: xi(nr,nt,np),eta(nr,nt,np),zeta(nr,nt,np) ! syn model (ani)
|
||||
double precision :: xiT(nr,nt,np),etaT(nr,nt,np),zetaT(nr,nt,np) ! true model (ani)
|
||||
double precision :: sigma1,sigma2,psi
|
||||
double precision,parameter :: slow_p=0.04,ani_p=0.03
|
||||
|
||||
! Eikonal solver
|
||||
double precision :: aT(nr,nt,np),bT(nr,nt,np),cT(nr,nt,np),fT(nr,nt,np),funT(nr,nt,np) ! true model 真实模型
|
||||
double precision :: a(nr,nt,np),b(nr,nt,np),c(nr,nt,np),f(nr,nt,np),fun(nr,nt,np) ! syn model 猜测模型
|
||||
double precision :: uT(nr,nt,np),TableT(nr,nt,np) !true timetable 真实走时场
|
||||
double precision :: u(nr,nt,np),Table(nr,nt,np) !syn timetable 猜测走时场
|
||||
!double precision :: T0para(8),tau(nr,nt,np) ! multiplicative factor
|
||||
|
||||
! adjoint source
|
||||
double precision,allocatable :: sourceADJ(:),TtimeT(:,:),Ttime(:,:) ! adjoint source 伴随源,真实走时，合成走时
|
||||
double precision :: TableADJ(nr,nt,np) ! adjoint field 伴随场
|
||||
double precision :: Ks(nr,nt,np),Kxi(nr,nt,np),Keta(nr,nt,np) ! event kernel
|
||||
integer,parameter :: nk = 3 ! number of kernels
|
||||
double precision :: all_Ks(nr,nt,np),all_Kxi(nr,nt,np),all_Keta(nr,nt,np) ! sensitivity kernel
|
||||
double precision :: all_Kernel(nr,nt,np,nk) ! kernels for all parameters together
|
||||
!double precision,parameter :: radius = 40 ! kernel mask radius
|
||||
|
||||
! inversion grid
|
||||
integer,parameter :: ninvr=11,ninvt=10,ninvp=10 ! inversion grid size (coarse)
|
||||
double precision,parameter :: invr1=6070.0,invr2=6400.0
|
||||
double precision,parameter :: invt1=30.0/180*pi,invt2=50.0/180*pi
|
||||
double precision,parameter :: invp1=15.0/180*pi,invp2=40.0/180*pi
|
||||
integer,parameter :: ngrid=5 ! number of nultigrid (multigrid technique)
|
||||
double precision :: invr(ngrid,ninvr),invt(ngrid,ninvt),invp(ngrid,ninvp),dinvr,dinvt,dinvp
|
||||
double precision :: update_value(nr,nt,np,nk) ! parameter update value 更新参数的变化量
|
||||
|
||||
! model update (optimization)
|
||||
double precision :: stepsize ! stepsize
|
||||
integer,parameter :: MaxIter=1 ! max iteration step
|
||||
double precision :: old_obj, obj, sou_obj ! 优化目标函数 objective function
|
||||
double precision,allocatable :: weight_sou(:),weight_rec(:) !weight function
|
||||
double precision :: dis_ij, dis_zero !weight function
|
||||
logical :: weight_sou_bool=.false. , weight_rec_bool= .false.
|
||||
|
||||
! temp var
|
||||
double precision :: depth,lat,lon
|
||||
|
||||
! output file
|
||||
character(Len=80) :: filename,form,form2
|
||||
|
||||
! loop index
|
||||
integer :: iir,iit,iip,idi,idj,idk,i,j,k,iter,igrid
|
||||
|
||||
! computing time
|
||||
double precision :: time_begin,time_end,alpha
|
||||
|
||||
! mpi parameter
|
||||
integer :: ierr,myid,nproc
|
||||
|
||||
! ############################# main work #############################
|
||||
|
||||
call mpi_init(ierr)
|
||||
|
||||
call mpi_comm_rank(mpi_comm_world,myid,ierr)
|
||||
call mpi_comm_size(mpi_comm_world,nproc,ierr)
|
||||
|
||||
call CPU_TIME(time_begin) ! program start
|
||||
|
||||
|
||||
|
||||
! ################### read sources and receivers 读取地震台站数据 ###################
|
||||
open(10,file='ega5/input/STATIONS.txt')
|
||||
read(10,*) nsou
|
||||
allocate(rsou(nsou),tsou(nsou),psou(nsou),weight_sou(nsou))
|
||||
do i=1,nsou
|
||||
read(10,*) depth,lat,lon
|
||||
rsou(i) = 6371.0-depth
|
||||
tsou(i) = lat/180.0*pi
|
||||
psou(i) = lon/180.0*pi
|
||||
end do
|
||||
close(10)
|
||||
|
||||
open(10,file='ega5/input/EARTHQUAKES.txt')
|
||||
read(10,*) nrec
|
||||
allocate(rrec(nrec),trec(nrec),prec(nrec),weight_rec(nrec))
|
||||
do i=1,nrec
|
||||
read(10,*) depth,lat,lon
|
||||
rrec(i) = 6371.0-depth
|
||||
trec(i) = lat/180.0*pi
|
||||
prec(i) = lon/180.0*pi
|
||||
end do
|
||||
close(10)
|
||||
|
||||
! distance based weight -rec 台站权重
|
||||
if (weight_rec_bool) then
|
||||
dis_zero = 0
|
||||
do i=1,nrec-1
|
||||
do j=i,nrec
|
||||
call Epicenter_Distance(trec(i),prec(i),trec(j),prec(j),dis_ij)
|
||||
dis_zero = dis_zero + dis_ij
|
||||
end do
|
||||
end do
|
||||
dis_zero = dis_zero/nrec/(nrec-1)*2
|
||||
dis_zero = dis_zero/2
|
||||
|
||||
do i=1,nrec
|
||||
weight_rec(i)=0.0
|
||||
do j=1,nrec
|
||||
call Epicenter_Distance(trec(i),prec(i),trec(j),prec(j),dis_ij)
|
||||
weight_rec(i) = weight_rec(i) + exp(-(dis_ij/dis_zero)**2)
|
||||
end do
|
||||
weight_rec(i) = 1.0/weight_rec(i)
|
||||
end do
|
||||
print *, dis_zero
|
||||
end if
|
||||
|
||||
if (weight_rec_bool) then
|
||||
! distance based weight - soruce 地震权重
|
||||
dis_zero = 0
|
||||
do i=1,nsou-1
|
||||
do j=i,nsou
|
||||
call Epicenter_Distance(tsou(i),psou(i),tsou(j),psou(j),dis_ij)
|
||||
dis_zero = dis_zero + dis_ij
|
||||
end do
|
||||
end do
|
||||
dis_zero = dis_zero/nsou/(nsou-1)*2
|
||||
dis_zero = dis_zero/4
|
||||
|
||||
do i=1,nsou
|
||||
weight_sou(i)=0.0
|
||||
do j=1,nsou
|
||||
call Epicenter_Distance(tsou(i),psou(i),tsou(j),psou(j),dis_ij)
|
||||
weight_sou(i) = weight_sou(i) + exp(-(dis_ij/dis_zero)**2)
|
||||
end do
|
||||
weight_sou(i) = 1.0/weight_sou(i)
|
||||
end do
|
||||
print *, dis_zero
|
||||
end if
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (myid .eq. 0) then
|
||||
open(100,file='ega5/output/STATIONS')
|
||||
open(101,file='ega5/output/EARTHQUAKES')
|
||||
do i=1,nsou
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7)') rsou(i),tsou(i),psou(i),weight_sou(i)
|
||||
end do
|
||||
do i=1,nrec
|
||||
write(101,'(f13.7,f13.7,f13.7,f13.7)') rrec(i),trec(i),prec(i),weight_rec(i)
|
||||
end do
|
||||
close(100);close(101)
|
||||
end if
|
||||
|
||||
! ######################### 生成网格 build mesh grid #####################################
|
||||
! -------- forward modeling grid ----------
|
||||
dr=(rr2-rr1)/(nr-1); dt=(tt2-tt1)/(nt-1); dp=(pp2-pp1)/(np-1)
|
||||
do iir=1,nr
|
||||
rr(iir)=rr1+(iir-1)*dr
|
||||
end do
|
||||
do iit=1,nt
|
||||
tt(iit)=tt1+(iit-1)*dt
|
||||
end do
|
||||
do iip=1,np
|
||||
pp(iip)=pp1+(iip-1)*dp
|
||||
end do
|
||||
|
||||
! -------- inversion multigrid ----------
|
||||
dinvr=(invr2-invr1)/(ninvr-1); dinvt=(invt2-invt1)/(ninvt-1); dinvp=(invp2-invp1)/(ninvp-1)
|
||||
do igrid=1,ngrid
|
||||
do iir=1,ninvr
|
||||
invr(igrid,iir)=invr1+(iir-1)*dinvr-(igrid-1)*dinvr/ngrid
|
||||
end do
|
||||
do iit=1,ninvt
|
||||
invt(igrid,iit)=invt1+(iit-1)*dinvt-(igrid-1)*dinvt/ngrid
|
||||
end do
|
||||
do iip=1,ninvp
|
||||
invp(igrid,iip)=invp1+(iip-1)*dinvp-(igrid-1)*dinvp/ngrid
|
||||
end do
|
||||
end do
|
||||
|
||||
! ######################### 构建背景模型 build the synthetic and true model #####################################
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
|
||||
! synthetic (initial) model
|
||||
eta(iir,iit,iip)=0.0;
|
||||
xi(iir,iit,iip)=0.0;
|
||||
zeta(iir,iit,iip)=gamma*sqrt(eta(iir,iit,iip)**2+xi(iir,iit,iip)**2)
|
||||
! if (rr(iir)>6351) then ! 6371 - 6351 20 km
|
||||
! fun(iir,iit,iip) = 1.0/(5.8+(6371-rr(iir))/20.0*0.7)
|
||||
! elseif (rr(iir)>6336) then ! 6351 - 6336 15 km
|
||||
! fun(iir,iit,iip) = 1.0/(6.5+(6351-rr(iir))/15.0*0.6)
|
||||
! elseif (rr(iir)>6251) then ! 6336 - 6251 85 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.04+(6336-rr(iir))/85.0*0.01)
|
||||
! elseif (rr(iir)>6161) then ! 6251 - 6161 90 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.05+(6251-rr(iir))/90.0*0.25)
|
||||
! elseif (rr(iir)>5961) then ! 6161 - 5961 200 km
|
||||
! fun(iir,iit,iip) = 1.0/(8.30+(6161-rr(iir))/200.0*0.73)
|
||||
! else
|
||||
! fun(iir,iit,iip) = 1.0/9.03
|
||||
! end if
|
||||
|
||||
if (rr(iir)>6351) then ! 6371 - 6351 20 km
|
||||
fun(iir,iit,iip) = 1.0/(5.8+(6371-rr(iir))/20.0*0.7)
|
||||
elseif (rr(iir)>6336) then ! 6351 - 6336 15 km
|
||||
fun(iir,iit,iip) = 1.0/(6.5+(6351-rr(iir))/15.0*0.6)
|
||||
elseif (rr(iir)>5961) then ! 6351 - 6336 15 km
|
||||
fun(iir,iit,iip) = 1.0/(8.0+(6336-rr(iir))/375.0*1)
|
||||
else
|
||||
fun(iir,iit,iip) = 1.0/9.0
|
||||
end if
|
||||
|
||||
|
||||
!read(100,*) xi(iir,iit,iip)
|
||||
!read(101,*) eta(iir,iit,iip)
|
||||
!read(102,*) fun(iir,iit,iip)
|
||||
|
||||
a(iir,iit,iip)=1.0+2*zeta(iir,iit,iip);
|
||||
b(iir,iit,iip)=1.0-2*xi(iir,iit,iip);
|
||||
c(iir,iit,iip)=1.0+2*xi(iir,iit,iip);
|
||||
f(iir,iit,iip)=-2*eta(iir,iit,iip);
|
||||
|
||||
Table(iir,iit,iip) = 0
|
||||
|
||||
|
||||
|
||||
! true (target) model
|
||||
if (tt(iit)>=30.0/180*pi .and. tt(iit)<=50.0/180*pi .and. &
|
||||
& pp(iip)>=15.0/180*pi .and. pp(iip)<=40.0/180*pi .and. &
|
||||
& rr(iir)>=6211.0 .and. rr(iir)<=6371.0 ) then
|
||||
sigma1 = sin(4*pi*(tt(iit)-30.0/180*pi)/(20.0/180*pi))* &
|
||||
& sin(4*pi*(pp(iip)-15.0/180*pi)/(25.0/180*pi))* &
|
||||
& sin(2*pi*(rr(iir)-6211)/160.0)
|
||||
else
|
||||
sigma1 = 0.0
|
||||
end if
|
||||
|
||||
|
||||
if (sigma1<0) then
|
||||
psi = 60.0/180*pi
|
||||
elseif (sigma1 > 0) then
|
||||
psi = 150.0/180*pi
|
||||
else
|
||||
psi = 0
|
||||
end if
|
||||
|
||||
etaT(iir,iit,iip)=ani_p*abs(sigma1)*sin(2*psi);
|
||||
xiT(iir,iit,iip)=ani_p*abs(sigma1)*cos(2*psi);
|
||||
zetaT(iir,iit,iip)=gamma*sqrt(etaT(iir,iit,iip)**2+xiT(iir,iit,iip)**2)
|
||||
|
||||
aT(iir,iit,iip)=1.0+2*zetaT(iir,iit,iip);
|
||||
bT(iir,iit,iip)=1.0-2*xiT(iir,iit,iip);
|
||||
cT(iir,iit,iip)=1.0+2*xiT(iir,iit,iip);
|
||||
fT(iir,iit,iip)=-2*etaT(iir,iit,iip);
|
||||
funT(iir,iit,iip) = fun(iir,iit,iip)/(1+sigma1*slow_p)
|
||||
|
||||
!fun(iir,iit,iip) = funT(iir,iit,iip)
|
||||
!eta(iir,iit,iip)=etaT(iir,iit,iip);
|
||||
!xi(iir,iit,iip)=xiT(iir,iit,iip);
|
||||
!zeta(iir,iit,iip)=zetaT(iir,iit,iip)
|
||||
!a(iir,iit,iip)=aT(iir,iit,iip)
|
||||
!b(iir,iit,iip)=bT(iir,iit,iip)
|
||||
!c(iir,iit,iip)=cT(iir,iit,iip)
|
||||
!f(iir,iit,iip)=fT(iir,iit,iip)
|
||||
|
||||
TableT(iir,iit,iip) = 0
|
||||
u(iir,iit,iip) = 0
|
||||
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (myid==0) then
|
||||
open(100,file='ega5/output/model_true')
|
||||
open(101,file='ega5/output/model_init')
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& funT(iir,iit,iip),xiT(iir,iit,iip),etaT(iir,iit,iip)
|
||||
write(101,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& fun(iir,iit,iip),xi(iir,iit,iip),eta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100);close(101)
|
||||
|
||||
! --------- 多重网格 multiple grid ------
|
||||
do igrid=1,Ngrid
|
||||
select case(igrid)
|
||||
case (1:9)
|
||||
write(form,'(I1)') igrid
|
||||
case (10:99)
|
||||
write(form,'(I2)') igrid
|
||||
end select
|
||||
open(100,file='ega5/output/multigrid'//trim(form))
|
||||
|
||||
do iir=1,ninvr
|
||||
do iit=1,ninvt
|
||||
do iip=1,ninvp
|
||||
write(100,'(f13.7,f13.7,f13.7)') &
|
||||
& invr(igrid,iir),invt(igrid,iit),invp(igrid,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end do
|
||||
|
||||
end if
|
||||
|
||||
|
||||
! ######################### 计算真实到时 calculate true traveltimes ######################
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
allocate(TtimeT(nsou,nrec)) ! 初始化真实到时表 initiate true traveltimes
|
||||
allocate(Ttime(nsou,nrec)) ! 初始化合成到时表 initiate syn traveltimes
|
||||
allocate(sourceADJ(nrec)) ! 初始化伴随源 initiate adjoint source
|
||||
|
||||
if (myid==0) then
|
||||
print *, ' '
|
||||
print *, '----------------- calculating true timetable ... ----------------'
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
do i=1,nsou ! loop sources (STATIONS)
|
||||
! -------- 求解程函方程 solve eikonal equations ------------
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
!rsou(i)=6371.0; tsou(i)=30.5/180.0*pi; psou(i)=15.5/180.0*pi
|
||||
call FSM_WENO3_PS_sphe_3d_mul_mpi(rr,tt,pp,nr,nt,np,aT,bT,cT,fT,TableT,funT,rsou(i),tsou(i),psou(i),u)
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
! -------- 得到真实走时 calculate true arrival time at receiver --------
|
||||
call Linear_Interp_3D(rr,tt,pp,TableT,nr,nt,np,rrec,trec,prec,TtimeT(i,:),nrec)
|
||||
!if ((myid.eq.0) .and. 1>0) then
|
||||
! print *, rsou(i),tsou(i)/pi*180,psou(i)/pi*180
|
||||
! open(100,file='ega5/output/arrivaltime')
|
||||
! do j=1,nrec
|
||||
! write(100,'(i5.3,f8.2,f6.2,f6.2,f8.3)') j, rrec(j),trec(j)/pi*180,prec(j)/pi*180,TtimeT(i,j)
|
||||
! end do
|
||||
! close(100)
|
||||
!end if
|
||||
end do
|
||||
|
||||
print *, '----------------- calculating true timetable over ---------------- '
|
||||
|
||||
! ######################## 反演开始 inversion start ##########################
|
||||
|
||||
! ----- 初始化反演参数 initiate inversion parameters ----
|
||||
stepsize = 0.01 ! 迭代步长 stepsize
|
||||
old_obj = 0; obj = 0 ! 目标函数 objective function
|
||||
|
||||
|
||||
|
||||
if (myid .eq. 0) then
|
||||
print *, ' '
|
||||
print *, '----------------- inversion start ... ----------------'
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
|
||||
|
||||
do iter = 1,MaxIter
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
if (myid .eq. 0) then
|
||||
print *, '----------------- iteration ',iter,' starting ... ----------------'
|
||||
end if
|
||||
|
||||
! ----- 初始化参数 initiate parameters ------
|
||||
all_Ks = 0; all_Kxi = 0; all_Keta = 0;
|
||||
obj = 0;
|
||||
|
||||
if (myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/misfit_step'//trim(form)
|
||||
open(998, file=trim(filename))
|
||||
end if
|
||||
|
||||
|
||||
do i=1,nsou ! loop sources (STATIONS)
|
||||
|
||||
! ######################## 计算合成走时场 calculate synthetic timetable ########################
|
||||
if (myid .eq. 0) then
|
||||
print *, '----------------- calculating synthetic timetable ... ----------------'
|
||||
end if
|
||||
|
||||
Table = 20
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
call FSM_WENO3_PS_sphe_3d_mul_mpi(rr,tt,pp,nr,nt,np,a,b,c,f,Table,fun,rsou(i),tsou(i),psou(i),u)
|
||||
call mpi_barrier(mpi_comm_world,ierr)
|
||||
! -------- 得到合成走时 calculate synthetic arrival time at receiver --------
|
||||
call Linear_Interp_3D(rr,tt,pp,Table,nr,nt,np,rrec,trec,prec,Ttime(i,:),nrec)
|
||||
|
||||
! -------- 构造伴随源 build adjoint source -------
|
||||
call Adjoint_Source_Dt(Ttime(i,:),TtimeT(i,:),nrec,sourceADJ,sou_obj) ! absolute traveltime difference
|
||||
if (myid .eq. 0) then
|
||||
do j=1,nrec
|
||||
write(998,'(f10.5)') Ttime(i,j)-TtimeT(i,j)
|
||||
end do
|
||||
end if
|
||||
|
||||
! weighting adjoint source
|
||||
if (weight_rec_bool) then
|
||||
do j=1,nrec
|
||||
sourceADJ(j) = sourceADJ(j) * weight_rec(j)
|
||||
end do
|
||||
end if
|
||||
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/syn_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7)') Table(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
!
|
||||
|
||||
!print *, Ttime(i,:),TtimeT(i,:)
|
||||
!call Adjoint_Source_Ddt(Ttime(i,:),TtimeT(i,:),nrec,sourceADJ,sou_obj) ! double difference traveltime
|
||||
!do j=1,nrec-1
|
||||
! do k=j,nrec
|
||||
! write(998,'(f10.5)') (Ttime(i,j)-Ttime(i,k))-(TtimeT(i,j)-TtimeT(i,k))
|
||||
! end do
|
||||
!end do
|
||||
|
||||
! ######################## 计算伴随场 adjoint field ########################
|
||||
if (myid .eq. 0) then
|
||||
! print *, '----------------- calculating adjoint field ... ----------------'
|
||||
end if
|
||||
call FSM_O1_Adj_sphe_3d(rr,tt,pp,nr,nt,np,Table,TableADJ,zeta,xi,eta,nrec,rrec,trec,prec,sourceADJ)
|
||||
!call FSM_O1_Adj_PS_sphe_3d(rr,tt,pp,nr,nt,np,T0para,tau,TableADJ,zeta,xi,eta,nrec,rrec,trec,prec,sourceADJ)
|
||||
! ---- 记录到 matlab 数据中 matlab record (adjoint field) ----
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/adj_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7)') TableADJ(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
! ######################## 计算敏感核 sensitivity kernel ########################
|
||||
!print *, '----------------- calculating kernel ... ----------------'
|
||||
call Sensitivity_Kernel(rr,tt,pp,nr,nt,np,Table,TableADJ,gamma,xi,eta,fun,Ks,Kxi,Keta)
|
||||
|
||||
! ------- 抹去伴随源处的大函数值 mask the source -------
|
||||
!print *, '----------------- kernel mask ----------------'
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Ks,rsou(i),tsou(i),psou(i),radius)
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Kxi,rsou(i),tsou(i),psou(i),radius)
|
||||
!call Kernel_Mask(rr,tt,pp,nr,nt,np,Keta,rsou(i),tsou(i),psou(i),radius)
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Ks,rsou(i),tsou(i),psou(i))
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Kxi,rsou(i),tsou(i),psou(i))
|
||||
call Kernel_Mask_new(rr,tt,pp,nr,nt,np,Keta,rsou(i),tsou(i),psou(i))
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record (adjoint field) ----
|
||||
if (1<0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
select case (i)
|
||||
case (1:9)
|
||||
write(form2,'(I1)') i
|
||||
case (10:99)
|
||||
write(form2,'(I2)') i
|
||||
end select
|
||||
filename='ega5/output/kernel_step'//trim(form)//'_event'//trim(form2)
|
||||
open(100,file=trim(filename))
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& Ks(iir,iit,iip),Kxi(iir,iit,iip),Keta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
! --------- 敏感核,obj叠加 sum kernels and objective function -------
|
||||
if (weight_sou_bool) then ! no weight
|
||||
all_Ks = all_Ks + Ks * weight_sou(i);
|
||||
all_Kxi = all_Kxi + Kxi * weight_sou(i);
|
||||
all_Keta = all_Keta + Keta * weight_sou(i);
|
||||
obj = obj + sou_obj !* weight_sou(i)
|
||||
else ! source weighted
|
||||
all_Ks = all_Ks + Ks;
|
||||
all_Kxi = all_Kxi + Kxi;
|
||||
all_Keta = all_Keta + Keta;
|
||||
obj = obj + sou_obj
|
||||
end if
|
||||
|
||||
end do
|
||||
|
||||
close(998)
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record (kernel) ----
|
||||
if (1>0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/kernel_step'//trim(form)//'_sum'
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& all_Ks(iir,iit,iip),all_Kxi(iir,iit,iip),all_Keta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
! ##################### 模型更新 model update ####################
|
||||
print *, '----------------- model updating ... ----------------'
|
||||
|
||||
all_Kernel(:,:,:,1) = all_Ks;
|
||||
all_Kernel(:,:,:,2) = all_Kxi;
|
||||
all_Kernel(:,:,:,3) = all_Keta;
|
||||
|
||||
! ------------ 更新速度(慢度) update velocity (slowness) ------------
|
||||
call Parameter_Update_Multigrid(rr,tt,pp,nr,nt,np,all_Kernel,nk, &
|
||||
& invr,invt,invp,ninvr,ninvt,ninvp,ngrid,stepsize,update_value)
|
||||
|
||||
if (1<0 .and. myid .eq. 0) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/model_update_step'//trim(form)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& -fun(iir,iit,iip)*update_value(iir,iit,iip,1), &
|
||||
& -update_value(iir,iit,iip,2),-update_value(iir,iit,iip,3)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
fun(iir,iit,iip) = fun(iir,iit,iip)*(1-update_value(iir,iit,iip,1))
|
||||
!fun(iir,iit,iip) = fun(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ------------ 更新xi update xi ------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
xi(iir,iit,iip) = xi(iir,iit,iip)-update_value(iir,iit,iip,2)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ------------ 更新eta update eta ------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
eta(iir,iit,iip) = eta(iir,iit,iip)-update_value(iir,iit,iip,3)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
! ----------- 更新 update eikonal solver paramater -----------------
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
b(iir,iit,iip)=1.0-2*xi(iir,iit,iip);
|
||||
c(iir,iit,iip)=1.0+2*xi(iir,iit,iip);
|
||||
f(iir,iit,iip)=-2*eta(iir,iit,iip);
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
|
||||
|
||||
|
||||
! ##################### 调整下降步长 modify stepsize #############
|
||||
if (myid .eq. 0) then
|
||||
print *, ' '
|
||||
end if
|
||||
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
open(999,file='ega5/output/obj',access='append')
|
||||
write(999,'(f9.2,f9.6)') obj, stepsize
|
||||
close(999)
|
||||
end if
|
||||
|
||||
if (iter == 1 ) then
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2)') 'iter 1, obj is', obj
|
||||
write(*,'(a,f9.6)') 'iter 1, stepsize is', stepsize
|
||||
end if
|
||||
elseif (iter >= 2 .and. obj < old_obj) then
|
||||
!stepsize = min(0.01,stepsize*1.2)
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2,a,f9.2)') 'objective function decreases, from', old_obj, ' to', obj
|
||||
write(*,'(a,f9.6)') 'new stepsize is ', stepsize
|
||||
end if
|
||||
elseif (iter >= 2 .and. obj >= old_obj) then
|
||||
!stepsize = max(0.002,stepsize*0.5)
|
||||
if (myid .eq. 0) then
|
||||
write(*,'(a,f9.2,a,f9.2)') 'objective function increases, from', old_obj, ' to', obj
|
||||
write(*,'(a,f9.6)') 'new stepsize is ', stepsize
|
||||
end if
|
||||
end if
|
||||
|
||||
print *, '----------------- iteration ',iter,' over ----------------'
|
||||
print *, ' '
|
||||
print *, ' '
|
||||
|
||||
|
||||
old_obj = obj
|
||||
|
||||
! ---- 记录到 matlab 数据中 matlab record ----
|
||||
if (1>0 .and. (myid .eq. 0)) then
|
||||
select case (iter)
|
||||
case (1:9)
|
||||
write(form,'(I1)') iter
|
||||
case (10:99)
|
||||
write(form,'(I2)') iter
|
||||
end select
|
||||
filename='ega5/output/model_step'//trim(form)
|
||||
open(100,file=trim(filename))
|
||||
do iir=1,nr
|
||||
do iit=1,nt
|
||||
do iip=1,np
|
||||
write(100,'(f13.7,f13.7,f13.7,f13.7,f13.7,f13.7)') &
|
||||
& rr(iir),tt(iit),pp(iip), &
|
||||
& fun(iir,iit,iip),xi(iir,iit,iip),eta(iir,iit,iip)
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
close(100)
|
||||
end if
|
||||
|
||||
|
||||
if (myid .eq. 0) then
|
||||
call CPU_TIME(time_end)
|
||||
write(*,'(f10.2)') time_end - time_begin
|
||||
end if
|
||||
|
||||
end do
|
||||
|
||||
|
||||
call mpi_finalize(ierr)
|
||||
|
||||
end program eikonal_2d
|
||||
|
||||
2838
test/old_tests/inversion_2_one_src/fortran_code/eikon_solver_mpi.f90
Normal file
2838
test/old_tests/inversion_2_one_src/fortran_code/eikon_solver_mpi.f90
Normal file
File diff suppressed because it is too large
Load Diff
56
test/old_tests/inversion_2_one_src/input_params.yml
Normal file
56
test/old_tests/inversion_2_one_src/input_params.yml
Normal file
@@ -0,0 +1,56 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'OUTPUT_FILES/src_rec_file_forward.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [11,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [30.0,50.0] # latitude in degree
|
||||
min_max_lon_inv : [15.0,40.0] # longitude in degree
|
||||
|
||||
#smooth_method : 1 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
#l_smooth_rtp : [0.9,0.9,0.9] # smoothing coefficients for each direction
|
||||
|
||||
max_iterations_inv : 1 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
use_gpu : 0
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 1000
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
is_output_source_field : 1 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
|
||||
is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
|
||||
is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
|
||||
|
||||
inv_strategy :
|
||||
is_inv_slowness : 1
|
||||
is_inv_azi_ani : 1
|
||||
is_inv_rad_ani : 1
|
||||
|
||||
54
test/old_tests/inversion_2_one_src/input_params2.yml
Normal file
54
test/old_tests/inversion_2_one_src/input_params2.yml
Normal file
@@ -0,0 +1,54 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'OUTPUT_FILES/src_rec_file_forward.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [11,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [30.0,50.0] # latitude in degree
|
||||
min_max_lon_inv : [15.0,40.0] # longitude in degree
|
||||
|
||||
#smooth_method : 1 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
#l_smooth_rtp : [0.9,0.9,0.9] # smoothing coefficients for each direction
|
||||
|
||||
max_iterations_inv : 1 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,1,1] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
use_gpu : 0
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 1000
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
it_output_suorce_field : 1
|
||||
is_output_model_dat : 1
|
||||
|
||||
inv_strategy :
|
||||
is_inv_slowness : 1
|
||||
is_inv_azi_ani : 1
|
||||
is_inv_rad_ani : 1
|
||||
40
test/old_tests/inversion_2_one_src/input_params_pre.yml
Normal file
40
test/old_tests/inversion_2_one_src/input_params_pre.yml
Normal file
@@ -0,0 +1,40 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
is_output_source_field : 1 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
|
||||
is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
|
||||
is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
|
||||
|
||||
36
test/old_tests/inversion_2_one_src/input_params_pre2.yml
Normal file
36
test/old_tests/inversion_2_one_src/input_params_pre2.yml
Normal file
@@ -0,0 +1,36 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,1,1] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
279
test/old_tests/inversion_2_one_src/make_test_model.ipynb
Normal file
279
test/old_tests/inversion_2_one_src/make_test_model.ipynb
Normal file
@@ -0,0 +1,279 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"R_earth = 6371.0 #6378.1370\n",
|
||||
"\n",
|
||||
"rr1=6070\n",
|
||||
"rr2=6400\n",
|
||||
"tt1=(30.0-1.5)/180*math.pi\n",
|
||||
"tt2=(50.0+1.5)/180*math.pi\n",
|
||||
"pp1=(15.0-1.5)/180*math.pi\n",
|
||||
"pp2=(40.0+1.5)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [55,55,55]\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[0]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[2]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"#s0 = 1.0/6.0\n",
|
||||
"slow_p=0.04\n",
|
||||
"ani_p=0.03\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ir,it,ip] = 0.0\n",
|
||||
" #xi_init[ir,it,ip] = 0.0\n",
|
||||
" zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)\n",
|
||||
" \n",
|
||||
" if (rr[ir]>6351):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)\n",
|
||||
" elif (rr[ir]>6336):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)\n",
|
||||
" elif (rr[ir]>5961):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1) \n",
|
||||
" else:\n",
|
||||
" fun_init[ir,it,ip] = 1.0/9.0\n",
|
||||
"\n",
|
||||
" vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \\\n",
|
||||
" and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 150.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)\n",
|
||||
" fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip] \n",
|
||||
"\n",
|
||||
"\n",
|
||||
"r_earth = R_earth #6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(r_earth-rr1,r_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init)\n",
|
||||
"fout_init.create_dataset('zeta',data=zeta_init)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true)\n",
|
||||
"fout_true.create_dataset('zeta',data=zeta_true)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(123456789)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 1\n",
|
||||
"n_rec = [1 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"dep_srcs=[12.902894]\n",
|
||||
"lon_srcs=[16.794572]\n",
|
||||
"lat_srcs=[37.503373]\n",
|
||||
"\n",
|
||||
"elev_recs = [0.0]\n",
|
||||
"lon_recs = [29.812050]\n",
|
||||
"lat_recs = [36.472809]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" dep = dep_srcs[i_src]\n",
|
||||
" lon = lon_srcs[i_src]\n",
|
||||
" lat = lat_srcs[i_src]\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy+\"_\"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
215
test/old_tests/inversion_2_one_src/make_test_model.py
Normal file
215
test/old_tests/inversion_2_one_src/make_test_model.py
Normal file
@@ -0,0 +1,215 @@
|
||||
# %% [markdown]
|
||||
# # notebook for create init and true test model
|
||||
|
||||
# %%
|
||||
import numpy as np
|
||||
import math
|
||||
|
||||
# grid
|
||||
R_earth = 6371.0 #6378.1370
|
||||
|
||||
rr1=6070
|
||||
rr2=6400
|
||||
tt1=(30.0-1.5)/180*math.pi
|
||||
tt2=(50.0+1.5)/180*math.pi
|
||||
pp1=(15.0-1.5)/180*math.pi
|
||||
pp2=(40.0+1.5)/180*math.pi
|
||||
|
||||
n_rtp = [55,55,55]
|
||||
dr = (rr2-rr1)/(n_rtp[0]-1)
|
||||
dt = (tt2-tt1)/(n_rtp[1]-1)
|
||||
dp = (pp2-pp1)/(n_rtp[2]-1)
|
||||
rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])
|
||||
tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
|
||||
pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])
|
||||
|
||||
# initial model
|
||||
gamma = 0.0
|
||||
#s0 = 1.0/6.0
|
||||
slow_p=0.04
|
||||
ani_p=0.03
|
||||
|
||||
eta_init = np.zeros(n_rtp)
|
||||
xi_init = np.zeros(n_rtp)
|
||||
zeta_init = np.zeros(n_rtp)
|
||||
fun_init = np.zeros(n_rtp)
|
||||
vel_init = np.zeros(n_rtp)
|
||||
|
||||
# true model
|
||||
eta_true = np.zeros(n_rtp)
|
||||
xi_true = np.zeros(n_rtp)
|
||||
zeta_true = np.zeros(n_rtp)
|
||||
fun_true = np.zeros(n_rtp)
|
||||
vel_true = np.zeros(n_rtp)
|
||||
|
||||
c=0
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
#eta_init[ir,it,ip] = 0.0
|
||||
#xi_init[ir,it,ip] = 0.0
|
||||
zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)
|
||||
|
||||
if (rr[ir]>6351):
|
||||
fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)
|
||||
elif (rr[ir]>6336):
|
||||
fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)
|
||||
elif (rr[ir]>5961):
|
||||
fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1)
|
||||
else:
|
||||
fun_init[ir,it,ip] = 1.0/9.0
|
||||
|
||||
vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]
|
||||
|
||||
# true model
|
||||
if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \
|
||||
and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \
|
||||
and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):
|
||||
c+=1
|
||||
sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \
|
||||
*math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \
|
||||
*math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)
|
||||
else:
|
||||
sigma = 0.0
|
||||
|
||||
if sigma < 0:
|
||||
psi = 60.0/180.0*math.pi
|
||||
elif sigma > 0:
|
||||
psi = 150.0/180.0*math.pi
|
||||
else:
|
||||
psi = 0.0
|
||||
|
||||
eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)
|
||||
xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)
|
||||
zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)
|
||||
fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)
|
||||
vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip]
|
||||
|
||||
|
||||
|
||||
r_earth = R_earth #6378.1370
|
||||
print("depminmax {} {}".format(r_earth-rr1,r_earth-rr2))
|
||||
print(c)
|
||||
|
||||
|
||||
# %%
|
||||
# write out
|
||||
import h5py
|
||||
|
||||
fout_init = h5py.File('test_model_init.h5', 'w')
|
||||
fout_true = h5py.File('test_model_true.h5', 'w')
|
||||
|
||||
# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
|
||||
fout_init.create_dataset('eta', data=eta_init)
|
||||
fout_init.create_dataset('xi', data=xi_init)
|
||||
fout_init.create_dataset('zeta',data=zeta_init)
|
||||
fout_init.create_dataset('vel', data=vel_init)
|
||||
|
||||
# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
|
||||
fout_true.create_dataset('eta', data=eta_true)
|
||||
fout_true.create_dataset('xi', data=xi_true)
|
||||
fout_true.create_dataset('zeta',data=zeta_true)
|
||||
fout_true.create_dataset('vel', data=vel_true)
|
||||
|
||||
fout_init.close()
|
||||
fout_true.close()
|
||||
|
||||
|
||||
# %% [markdown]
|
||||
# # prepare src station file
|
||||
#
|
||||
# ```
|
||||
# 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event
|
||||
# 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec
|
||||
# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
|
||||
# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
|
||||
#
|
||||
# ```
|
||||
|
||||
# %%
|
||||
import random
|
||||
random.seed(123456789)
|
||||
|
||||
# dummys
|
||||
year_dummy = 1998
|
||||
month_dummy = 1
|
||||
day_dummy = 1
|
||||
hour_dummy = 0
|
||||
minute_dummy = 0
|
||||
second_dummy = 0
|
||||
mag_dummy = 3.0
|
||||
id_dummy = 1000
|
||||
st_name_dummy = 'AAAA'
|
||||
phase_dummy = 'P'
|
||||
arriv_t_dummy = 0.0
|
||||
|
||||
tt1deg = tt1 * 180.0/math.pi
|
||||
tt2deg = tt2 * 180.0/math.pi
|
||||
pp1deg = pp1 * 180.0/math.pi
|
||||
pp2deg = pp2 * 180.0/math.pi
|
||||
|
||||
|
||||
n_src = 1
|
||||
n_rec = [1 for x in range(n_src)]
|
||||
|
||||
|
||||
lines = []
|
||||
|
||||
pos_src=[]
|
||||
pos_rec=[]
|
||||
|
||||
dep_srcs=[12.902894]
|
||||
lon_srcs=[16.794572]
|
||||
lat_srcs=[37.503373]
|
||||
|
||||
elev_recs = [0.0]
|
||||
lon_recs = [29.812050]
|
||||
lat_recs = [36.472809]
|
||||
|
||||
|
||||
# create dummy src
|
||||
for i_src in range(n_src):
|
||||
# define one point in the domain (rr1 bottom, rr2 top)
|
||||
dep = dep_srcs[i_src]
|
||||
lon = lon_srcs[i_src]
|
||||
lat = lat_srcs[i_src]
|
||||
|
||||
src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]
|
||||
lines.append(src)
|
||||
|
||||
pos_src.append([lon,lat,dep])
|
||||
|
||||
# create dummy station
|
||||
for i_rec in range(n_rec[i_src]):
|
||||
#elev_rec = random.uniform(0.0,-10.0) # elevation in m
|
||||
#lon_rec = random.uniform(pp1deg,pp2deg)
|
||||
#lat_rec = random.uniform(tt1deg,tt2deg)
|
||||
|
||||
rec = [i_src, i_rec, st_name_dummy+"_"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, arriv_t_dummy]
|
||||
lines.append(rec)
|
||||
|
||||
pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])
|
||||
|
||||
# write out ev_arrivals file
|
||||
fname = 'src_rec_test.dat'
|
||||
|
||||
with open(fname, 'w') as f:
|
||||
for line in lines:
|
||||
for elem in line:
|
||||
f.write('{} '.format(elem))
|
||||
f.write('\n')
|
||||
|
||||
|
||||
# %%
|
||||
# draw src and rec positions
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
for i_src in range(n_src):
|
||||
plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
|
||||
|
||||
# %%
|
||||
# plot receivers
|
||||
for i_rec in range(n_rec[0]):
|
||||
plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
|
||||
|
||||
|
||||
14
test/old_tests/inversion_ASCII/README.md
Normal file
14
test/old_tests/inversion_ASCII/README.md
Normal file
@@ -0,0 +1,14 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` for creating
|
||||
- source, receiver file
|
||||
- true model
|
||||
- initial model
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
-> this will output src_rec_result.dat file which includes the arrival time at each station
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`.
|
||||
|
||||
66
test/old_tests/inversion_ASCII/check_obj_func.ipynb
Normal file
66
test/old_tests/inversion_ASCII/check_obj_func.ipynb
Normal file
@@ -0,0 +1,66 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# check the change of objective values\n",
|
||||
"\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"fpath='objective_function.txt'\n",
|
||||
"\n",
|
||||
"objs=[]\n",
|
||||
"\n",
|
||||
"with open(fpath) as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" for l in lines:\n",
|
||||
" if(l.startswith('i_inv')):\n",
|
||||
" continue\n",
|
||||
" objs.append(float(l.strip().split(',')[1]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"plt.xlabel('iteration')\n",
|
||||
"plt.ylabel('objective function value')\n",
|
||||
"plt.plot(objs)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
185
test/old_tests/inversion_ASCII/check_src_rec_file.ipynb
Normal file
185
test/old_tests/inversion_ASCII/check_src_rec_file.ipynb
Normal file
@@ -0,0 +1,185 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# read src_rec file and check its arrival time and distance from src to rec\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"def read_src_rec_file(fpath):\n",
|
||||
"\n",
|
||||
" with open(fpath, \"r\") as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" # list to store src lon lat\n",
|
||||
" src_pos = []\n",
|
||||
" # list to store rec lon lat\n",
|
||||
" rec_pos_tmp=[]\n",
|
||||
" rec_pos = []\n",
|
||||
"\n",
|
||||
" for line in lines:\n",
|
||||
" # src line if there are 13 elements\n",
|
||||
" if len(line.split()) == 13:\n",
|
||||
" # store source lon lat dep\n",
|
||||
" stlon = float(line.split()[8])\n",
|
||||
" stlat = float(line.split()[7])\n",
|
||||
" src_pos.append([stlon, stlat])\n",
|
||||
"\n",
|
||||
" nrec = float(line.split()[11])\n",
|
||||
" # rec line if there are 9 elements\n",
|
||||
" elif len(line.split()) == 9:\n",
|
||||
" # store receiver lon lat dep\n",
|
||||
" rclon = float(line.split()[4])\n",
|
||||
" rclat = float(line.split()[3])\n",
|
||||
" rctime= float(line.split()[8])\n",
|
||||
" # calc epicentral distance from src\n",
|
||||
" dist = np.sqrt((stlon-rclon)**2 + (stlat-rclat)**2)\n",
|
||||
" rec_pos_tmp.append([rclon, rclat, rctime, dist])\n",
|
||||
"\n",
|
||||
" nrec-=1\n",
|
||||
" else:\n",
|
||||
" raise ValueError(\"src_rec_test_out.dat file is not correct\")\n",
|
||||
"\n",
|
||||
" if nrec==0:\n",
|
||||
" rec_pos.append(rec_pos_tmp)\n",
|
||||
" # remove all rec_pos_tmp\n",
|
||||
" rec_pos_tmp = []\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" src_pos = np.array(src_pos)\n",
|
||||
" rec_pos = np.array(rec_pos)\n",
|
||||
"\n",
|
||||
" return src_pos, rec_pos"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"src_pos_true, rec_pos_true = read_src_rec_file(\"./src_rec_test_out.dat\")\n",
|
||||
"src_pos_try, rec_pos_try = read_src_rec_file(\"./src_rec_test_out_out.dat\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot rec_pos for each src_pos with color by 3rd element\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def plot_srcrec(src_pos, rec_pos):\n",
|
||||
"\n",
|
||||
" # selected source\n",
|
||||
" id_src = 1\n",
|
||||
" \n",
|
||||
" fig, axs = plt.subplots(2,1,figsize=(10,10))\n",
|
||||
" \n",
|
||||
" # plot arrival time\n",
|
||||
" # src\n",
|
||||
" axs[0].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
" # rec\n",
|
||||
" axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=10, marker='o')\n",
|
||||
" \n",
|
||||
" # colorbar\n",
|
||||
" cbar = plt.colorbar(axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=100, marker='o'))\n",
|
||||
" cbar.set_label('arrival time')\n",
|
||||
" \n",
|
||||
" # plot epicentral distance\n",
|
||||
" # src\n",
|
||||
" axs[1].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
" # rec\n",
|
||||
" axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=100, marker='o')\n",
|
||||
" \n",
|
||||
" # colorbar\n",
|
||||
" cbar = plt.colorbar(axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=10, marker='o'))\n",
|
||||
" cbar.set_label('epicentral distance')\n",
|
||||
" \n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"plot_srcrec(src_pos_true, rec_pos_true)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"plot_srcrec(src_pos_try, rec_pos_try)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_diff = rec_pos_true[:][:][2]-rec_pos_try[:][:][2]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_diff.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos_true.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
51
test/old_tests/inversion_ASCII/input_params.yml
Normal file
51
test/old_tests/inversion_ASCII/input_params.yml
Normal file
@@ -0,0 +1,51 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-2.863,17.137] # depth in km
|
||||
min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
optim_method : 0 # optimization method. 0 : "grad_descent", 1 : "lbfgs", 2 : "halve-stepping"
|
||||
smooth_method : 0 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
max_iterations_inv : 100 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
# parameters for multiparametric inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [5,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-10.0, 10.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [37.7,42.3] # latitude in degree
|
||||
min_max_lon_inv : [22.7,27.3] # longitude in degree
|
||||
# parameters for laplacian smoothing
|
||||
l_smooth_rtp : [10,10,10] # smoothing coefficients for each direction
|
||||
regularization_weight : 1.0 # regularization weight NOTWORKING
|
||||
# parameter for halving-stepping or lbfgs
|
||||
max_sub_iterations : 100 # maximum number of sub-iterations
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
use_gpu : 0 # 0: CPU, 1: GPU
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-6
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
37
test/old_tests/inversion_ASCII/input_params_pre.yml
Normal file
37
test/old_tests/inversion_ASCII/input_params_pre.yml
Normal file
@@ -0,0 +1,37 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-2.863,17.137] # depth in km
|
||||
min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.dat' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [2,1,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-6
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
output_file_format : 1 # 0: hdf5, 1: ascii
|
||||
|
||||
|
||||
338
test/old_tests/inversion_ASCII/make_test_model.ipynb
Normal file
338
test/old_tests/inversion_ASCII/make_test_model.ipynb
Normal file
@@ -0,0 +1,338 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"#R_earth = 6378.1370\n",
|
||||
"R_earth = 6371.0\n",
|
||||
"\n",
|
||||
"rr1=6361 \n",
|
||||
"rr2=6381\n",
|
||||
"tt1=(38.0-0.3)/180*math.pi\n",
|
||||
"tt2=(42.0+0.3)/180*math.pi\n",
|
||||
"pp1=(23.0-0.3)/180*math.pi\n",
|
||||
"pp2=(27.0+0.3)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [10,50,50]\n",
|
||||
"n_rtp.reverse()\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[2]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[0]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"s0 = 1.0/6.0\n",
|
||||
"slow_p=0.06\n",
|
||||
"ani_p=0.04\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"a_init = np.zeros(n_rtp)\n",
|
||||
"b_init = np.zeros(n_rtp)\n",
|
||||
"c_init = np.zeros(n_rtp)\n",
|
||||
"f_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"a_true = np.zeros(n_rtp)\n",
|
||||
"b_true = np.zeros(n_rtp)\n",
|
||||
"c_true = np.zeros(n_rtp)\n",
|
||||
"f_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ip,it,ir] = 0.0\n",
|
||||
" #xi_init[ip,it,ir] = 0.0\n",
|
||||
" zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)\n",
|
||||
" fun_init[ip,it,ir] = s0\n",
|
||||
" vel_init[ip,it,ir] = 1.0/s0\n",
|
||||
" a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]\n",
|
||||
" b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]\n",
|
||||
" c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]\n",
|
||||
" f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(2.0*math.pi*(tt[it]-38.0/180.0*math.pi)/(4.0/180.0*math.pi))*math.sin(2.0*math.pi*(pp[ip]-23.0/180.0*math.pi)/(4.0/180.0*math.pi))\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 120.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)\n",
|
||||
" fun_true[ip,it,ir] = s0/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir] \n",
|
||||
" a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]\n",
|
||||
" b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]\n",
|
||||
" c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]\n",
|
||||
" f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"#r_earth = 6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(R_earth-rr1,R_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out in ASCIII\n",
|
||||
"\n",
|
||||
"#\n",
|
||||
"\n",
|
||||
"fname_init = 'test_model_init.dat'\n",
|
||||
"fname_true = 'test_model_true.dat'\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write init model\n",
|
||||
"with open(fname_init, 'w') as f:\n",
|
||||
" # write nodes in rtp\n",
|
||||
" for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
|
||||
" f.write(\"{} {} {} {} {} {} {} {} {}\\n\".format(eta_init[ip,it,ir],xi_init[ip,it,ir],zeta_init[ip,it,ir],fun_init[ip,it,ir],vel_init[ip,it,ir],a_init[ip,it,ir],b_init[ip,it,ir],c_init[ip,it,ir],f_init[ip,it,ir]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write true model\n",
|
||||
"with open(fname_true, 'w') as f:\n",
|
||||
" # write nodes in rtp\n",
|
||||
" for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
|
||||
" f.write(\"{} {} {} {} {} {} {} {} {}\\n\".format(eta_true[ip,it,ir],xi_true[ip,it,ir],zeta_true[ip,it,ir],fun_true[ip,it,ir],vel_true[ip,it,ir],a_true[ip,it,ir],b_true[ip,it,ir],c_true[ip,it,ir],f_true[ip,it,ir]))\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(1145141919810)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 500\n",
|
||||
"n_rec = [30 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"nij_src = math.sqrt(n_src)\n",
|
||||
"nij_rec = math.sqrt(n_rec[0])\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create receiver coordinates\n",
|
||||
"elev_recs=[]\n",
|
||||
"lon_recs=[]\n",
|
||||
"lat_recs=[]\n",
|
||||
"rec_names=[]\n",
|
||||
"for i in range(n_rec[0]):\n",
|
||||
" #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
|
||||
" #elev_recs.append(0) # elevation in m\n",
|
||||
" #lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
|
||||
" #lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
|
||||
" rec_names.append(i)\n",
|
||||
" # regularly\n",
|
||||
" elev_recs.append(0.0)\n",
|
||||
" tmp_ilon = i%nij_rec\n",
|
||||
" tmp_ilat = int(i/nij_rec)\n",
|
||||
" lon_recs.append(pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec)\n",
|
||||
" lat_recs.append(tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" # random\n",
|
||||
" #dep = random.uniform((R_earth-rr1)*0.5,(R_earth-rr1)*0.98)\n",
|
||||
" #lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" # regularl\n",
|
||||
" dep = (R_earth-rr1)*0.9\n",
|
||||
" tmp_ilon = i_src%nij_src\n",
|
||||
" tmp_ilat = int(i_src/nij_src)\n",
|
||||
" lon = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_src\n",
|
||||
" lat = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_src\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = 0.0 #random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
" # regularly\n",
|
||||
" #elev_rec = -10.0\n",
|
||||
" #tmp_ilon = i_rec%nij_rec\n",
|
||||
" #tmp_ilat = int(i_rec/nij_rec)\n",
|
||||
" #lon_rec = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec\n",
|
||||
" #lat_rec = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec\n",
|
||||
"\n",
|
||||
" # \n",
|
||||
" elev_rec = elev_recs[i_rec]\n",
|
||||
" lon_rec = lon_recs[i_rec]\n",
|
||||
" lat_rec = lat_recs[i_rec]\n",
|
||||
" st_name_dummy = rec_names[i_rec]\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_rec,lat_rec,elev_rec])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "fbd0b2a7df497f398d93ab2f589d8a5daa3108cfb7ff2b90736653cca3aeadc0"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
94
test/old_tests/inversion_ASCII/view_result.ipynb
Normal file
94
test/old_tests/inversion_ASCII/view_result.ipynb
Normal file
@@ -0,0 +1,94 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np \n",
|
||||
"import sys\n",
|
||||
"sys.path.append(\"../../utils/\")\n",
|
||||
"\n",
|
||||
"from tomoatt_data_retrieval import get_data_from_ascii\n",
|
||||
"\n",
|
||||
"#\n",
|
||||
"# plot calculated travel time field\n",
|
||||
"\n",
|
||||
"# number of grids\n",
|
||||
"nx = 50 \n",
|
||||
"ny = 50\n",
|
||||
"nz = 10\n",
|
||||
"\n",
|
||||
"# read coordiantes from file\n",
|
||||
"fname_grid = \"OUTPUT_FILES/out_grid.out\"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# read data\n",
|
||||
"_src_id = 0\n",
|
||||
"_inv_id = 0\n",
|
||||
"\n",
|
||||
"# filling 0 for digit\n",
|
||||
"inv_id = str(_inv_id).zfill(4)\n",
|
||||
"src_id = str(_src_id).zfill(4)\n",
|
||||
"fname_data = \"OUTPUT_FILES/T_res_inv_{}_src_{}.dat\".format(inv_id, src_id)\n",
|
||||
"\n",
|
||||
"data = get_data_from_ascii(fname_data, fname_grid, nz, ny, nx, 2, 1,2, verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"fig, axs = plt.subplots(3, 1, figsize=(15, 5))\n",
|
||||
"\n",
|
||||
"axs[0].imshow(data[5,:,:], cmap='jet', interpolation='nearest')\n",
|
||||
"axs[0].set_title('lon-lat')\n",
|
||||
"\n",
|
||||
"axs[1].imshow(data[:,25,:], cmap='jet', interpolation='nearest')\n",
|
||||
"axs[1].set_title('r-lon')\n",
|
||||
"\n",
|
||||
"axs[2].imshow(data[:,:,25], cmap='jet', interpolation='nearest')\n",
|
||||
"axs[2].set_title('r-lat')\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
30
test/old_tests/inversion_one_src/README.md
Normal file
30
test/old_tests/inversion_one_src/README.md
Normal file
@@ -0,0 +1,30 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` or `make_test_model.py` for creating
|
||||
- source, receiver file (src_rec_test.dat)
|
||||
- true model (test_model_true.h5)
|
||||
- initial model (test_model_init.h5)
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
-> this will output src_rec_test_out.dat file which includes the true arrival times
|
||||
```bash
|
||||
mpirun --oversubscribe -np 8 ../../build/TOMOATT ./input_params_pre.yml
|
||||
```
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`.
|
||||
-> this will output src_rec_test_out.dat file which includes the true arrival times
|
||||
```bash
|
||||
mpirun --oversubscribe -np 8 ../../build/TOMOATT ./input_params_pre.yml
|
||||
```
|
||||
|
||||
4. for visualizing the result files
|
||||
```bash
|
||||
paraview out_data_sim_0.xmf
|
||||
```
|
||||
|
||||
0 is the source id. The kernel and model fields are output in the file of 0th source.
|
||||
|
||||
|
||||
|
||||
44
test/old_tests/inversion_one_src/input_params.yml
Normal file
44
test/old_tests/inversion_one_src/input_params.yml
Normal file
@@ -0,0 +1,44 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
min_max_dep : [-2.863,17.137] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [20,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 4 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [5,10,10] # number of the base inversion grid points
|
||||
optim_method : 0 # optimization method. 0 : "grad_descent" or 1 : "lbfgs"
|
||||
max_iterations_inv : 2 # maximum number of inversion iterations
|
||||
step_size : 0.01 # initial step size for inversion
|
||||
# parameters for laplacian iterative smoothing
|
||||
l_smooth_rtp : [0.9,0.9,0.9] # smoothing coefficients for each direction
|
||||
# parameters for lbfgs
|
||||
regularization_weight : 20.0 # regularization weight
|
||||
max_sub_iterations : 1 # maximum number of sub-iterations
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-10
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
35
test/old_tests/inversion_one_src/input_params_pre.yml
Normal file
35
test/old_tests/inversion_one_src/input_params_pre.yml
Normal file
@@ -0,0 +1,35 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
min_max_dep : [-2.863,17.137] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [20,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver (1: yes, 0: no)
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-10
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
319
test/old_tests/inversion_one_src/make_test_model.ipynb
Normal file
319
test/old_tests/inversion_one_src/make_test_model.ipynb
Normal file
@@ -0,0 +1,319 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"R_earth = 6378.1370\n",
|
||||
"\n",
|
||||
"rr1=6361 \n",
|
||||
"rr2=6381\n",
|
||||
"tt1=(38.0-0.3)/180*math.pi\n",
|
||||
"tt2=(42.0+0.3)/180*math.pi\n",
|
||||
"pp1=(23.0-0.3)/180*math.pi\n",
|
||||
"pp2=(27.0+0.3)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [20,50,50]\n",
|
||||
"n_rtp.reverse()\n",
|
||||
"dr = (rr2-rr1)/n_rtp[2]\n",
|
||||
"dt = (tt2-tt1)/n_rtp[1]\n",
|
||||
"dp = (pp2-pp1)/n_rtp[0]\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"s0 = 1.0/6.0\n",
|
||||
"slow_p=0.06\n",
|
||||
"ani_p=0.04\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"a_init = np.zeros(n_rtp)\n",
|
||||
"b_init = np.zeros(n_rtp)\n",
|
||||
"c_init = np.zeros(n_rtp)\n",
|
||||
"f_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"a_true = np.zeros(n_rtp)\n",
|
||||
"b_true = np.zeros(n_rtp)\n",
|
||||
"c_true = np.zeros(n_rtp)\n",
|
||||
"f_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ip,it,ir] = 0.0\n",
|
||||
" #xi_init[ip,it,ir] = 0.0\n",
|
||||
" zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)\n",
|
||||
" fun_init[ip,it,ir] = s0\n",
|
||||
" vel_init[ip,it,ir] = 1.0/s0\n",
|
||||
" a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]\n",
|
||||
" b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]\n",
|
||||
" c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]\n",
|
||||
" f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(2.0*math.pi*(tt[it]-38.0/180.0*math.pi)/(4.0/180.0*math.pi))*math.sin(2.0*math.pi*(pp[ip]-23.0/180.0*math.pi)/(4.0/180.0*math.pi))\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 120.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)\n",
|
||||
" fun_true[ip,it,ir] = s0/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir] \n",
|
||||
" a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]\n",
|
||||
" b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]\n",
|
||||
" c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]\n",
|
||||
" f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"r_earth = 6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(r_earth-rr1,r_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init.T)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init.T)\n",
|
||||
"fout_init.create_dataset('zeta', data=zeta_init.T)\n",
|
||||
"fout_init.create_dataset('fun', data=fun_init.T)\n",
|
||||
"fout_init.create_dataset('fac_a', data=a_init.T)\n",
|
||||
"fout_init.create_dataset('fac_b', data=b_init.T)\n",
|
||||
"fout_init.create_dataset('fac_c', data=c_init.T)\n",
|
||||
"fout_init.create_dataset('fac_f', data=f_init.T)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init.T)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true.T)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true.T)\n",
|
||||
"fout_true.create_dataset('zeta', data=zeta_true.T)\n",
|
||||
"fout_true.create_dataset('fun', data=fun_true.T)\n",
|
||||
"fout_true.create_dataset('fac_a', data=a_true.T)\n",
|
||||
"fout_true.create_dataset('fac_b', data=b_true.T)\n",
|
||||
"fout_true.create_dataset('fac_c', data=c_true.T)\n",
|
||||
"fout_true.create_dataset('fac_f', data=f_true.T)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true.T)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(1145141919810)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 1\n",
|
||||
"n_rec = [1 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"nij_src = math.sqrt(n_src)\n",
|
||||
"nij_rec = math.sqrt(n_rec[0])\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" # random\n",
|
||||
" #dep = random.uniform((R_earth-rr1)*0.95,(R_earth-rr1)*0.98)\n",
|
||||
" #lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
" # regularl\n",
|
||||
" dep = (R_earth-rr1)*0.9\n",
|
||||
" tmp_ilon = i_src%nij_src\n",
|
||||
" tmp_ilat = int(i_src/nij_src)\n",
|
||||
" lon = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_src\n",
|
||||
" lat = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_src\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" elev_rec = random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
" # regularly\n",
|
||||
" #elev_rec = -10.0\n",
|
||||
" #tmp_ilon = i_rec%nij_rec\n",
|
||||
" #tmp_ilat = int(i_rec/nij_rec)\n",
|
||||
" #lon_rec = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec\n",
|
||||
" #lat_rec = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy+str(i_rec), lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_rec,lat_rec,elev_rec])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "fbd0b2a7df497f398d93ab2f589d8a5daa3108cfb7ff2b90736653cca3aeadc0"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
246
test/old_tests/inversion_one_src/make_test_model.py
Normal file
246
test/old_tests/inversion_one_src/make_test_model.py
Normal file
@@ -0,0 +1,246 @@
|
||||
# %% [markdown]
|
||||
# # notebook for create init and true test model
|
||||
|
||||
# %%
|
||||
import numpy as np
|
||||
import math
|
||||
|
||||
# grid
|
||||
R_earth = 6378.1370
|
||||
|
||||
rr1=6361
|
||||
rr2=6381
|
||||
tt1=(38.0-0.3)/180*math.pi
|
||||
tt2=(42.0+0.3)/180*math.pi
|
||||
pp1=(23.0-0.3)/180*math.pi
|
||||
pp2=(27.0+0.3)/180*math.pi
|
||||
|
||||
n_rtp = [20,50,50]
|
||||
n_rtp.reverse()
|
||||
dr = (rr2-rr1)/n_rtp[2]
|
||||
dt = (tt2-tt1)/n_rtp[1]
|
||||
dp = (pp2-pp1)/n_rtp[0]
|
||||
rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])
|
||||
tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
|
||||
pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])
|
||||
|
||||
# initial model
|
||||
gamma = 0.0
|
||||
s0 = 1.0/6.0
|
||||
slow_p=0.06
|
||||
ani_p=0.04
|
||||
|
||||
eta_init = np.zeros(n_rtp)
|
||||
xi_init = np.zeros(n_rtp)
|
||||
zeta_init = np.zeros(n_rtp)
|
||||
fun_init = np.zeros(n_rtp)
|
||||
vel_init = np.zeros(n_rtp)
|
||||
a_init = np.zeros(n_rtp)
|
||||
b_init = np.zeros(n_rtp)
|
||||
c_init = np.zeros(n_rtp)
|
||||
f_init = np.zeros(n_rtp)
|
||||
|
||||
# true model
|
||||
eta_true = np.zeros(n_rtp)
|
||||
xi_true = np.zeros(n_rtp)
|
||||
zeta_true = np.zeros(n_rtp)
|
||||
fun_true = np.zeros(n_rtp)
|
||||
vel_true = np.zeros(n_rtp)
|
||||
a_true = np.zeros(n_rtp)
|
||||
b_true = np.zeros(n_rtp)
|
||||
c_true = np.zeros(n_rtp)
|
||||
f_true = np.zeros(n_rtp)
|
||||
|
||||
c=0
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
#eta_init[ip,it,ir] = 0.0
|
||||
#xi_init[ip,it,ir] = 0.0
|
||||
zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)
|
||||
fun_init[ip,it,ir] = s0
|
||||
vel_init[ip,it,ir] = 1.0/s0
|
||||
a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]
|
||||
b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]
|
||||
c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]
|
||||
f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]
|
||||
|
||||
# true model
|
||||
if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \
|
||||
and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):
|
||||
c+=1
|
||||
sigma = math.sin(2.0*math.pi*(tt[it]-38.0/180.0*math.pi)/(4.0/180.0*math.pi))*math.sin(2.0*math.pi*(pp[ip]-23.0/180.0*math.pi)/(4.0/180.0*math.pi))
|
||||
else:
|
||||
sigma = 0.0
|
||||
|
||||
if sigma < 0:
|
||||
psi = 60.0/180.0*math.pi
|
||||
elif sigma > 0:
|
||||
psi = 120.0/180.0*math.pi
|
||||
else:
|
||||
psi = 0.0
|
||||
|
||||
eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)
|
||||
xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)
|
||||
zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)
|
||||
fun_true[ip,it,ir] = s0/(1.0+sigma*slow_p)
|
||||
vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir]
|
||||
a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]
|
||||
b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]
|
||||
c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]
|
||||
f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]
|
||||
|
||||
|
||||
|
||||
r_earth = 6378.1370
|
||||
print("depminmax {} {}".format(r_earth-rr1,r_earth-rr2))
|
||||
print(c)
|
||||
|
||||
|
||||
# %%
|
||||
|
||||
|
||||
# %%
|
||||
# write out
|
||||
import h5py
|
||||
|
||||
fout_init = h5py.File('test_model_init.h5', 'w')
|
||||
fout_true = h5py.File('test_model_true.h5', 'w')
|
||||
|
||||
# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
|
||||
fout_init.create_dataset('eta', data=eta_init.T)
|
||||
fout_init.create_dataset('xi', data=xi_init.T)
|
||||
fout_init.create_dataset('zeta', data=zeta_init.T)
|
||||
fout_init.create_dataset('fun', data=fun_init.T)
|
||||
fout_init.create_dataset('fac_a', data=a_init.T)
|
||||
fout_init.create_dataset('fac_b', data=b_init.T)
|
||||
fout_init.create_dataset('fac_c', data=c_init.T)
|
||||
fout_init.create_dataset('fac_f', data=f_init.T)
|
||||
fout_init.create_dataset('vel', data=vel_init.T)
|
||||
|
||||
# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
|
||||
fout_true.create_dataset('eta', data=eta_true.T)
|
||||
fout_true.create_dataset('xi', data=xi_true.T)
|
||||
fout_true.create_dataset('zeta', data=zeta_true.T)
|
||||
fout_true.create_dataset('fun', data=fun_true.T)
|
||||
fout_true.create_dataset('fac_a', data=a_true.T)
|
||||
fout_true.create_dataset('fac_b', data=b_true.T)
|
||||
fout_true.create_dataset('fac_c', data=c_true.T)
|
||||
fout_true.create_dataset('fac_f', data=f_true.T)
|
||||
fout_true.create_dataset('vel', data=vel_true.T)
|
||||
|
||||
fout_init.close()
|
||||
fout_true.close()
|
||||
|
||||
|
||||
# %% [markdown]
|
||||
# # prepare src station file
|
||||
#
|
||||
# ```
|
||||
# 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event
|
||||
# 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec
|
||||
# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
|
||||
# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
|
||||
#
|
||||
# ```
|
||||
|
||||
# %%
|
||||
import random
|
||||
random.seed(1145141919810)
|
||||
|
||||
# dummys
|
||||
year_dummy = 1998
|
||||
month_dummy = 1
|
||||
day_dummy = 1
|
||||
hour_dummy = 0
|
||||
minute_dummy = 0
|
||||
second_dummy = 0
|
||||
mag_dummy = 3.0
|
||||
id_dummy = 1000
|
||||
st_name_dummy = 'AAAA'
|
||||
phase_dummy = 'P'
|
||||
dist_dummy = 100.0
|
||||
arriv_t_dummy = 0.0
|
||||
|
||||
tt1deg = tt1 * 180.0/math.pi
|
||||
tt2deg = tt2 * 180.0/math.pi
|
||||
pp1deg = pp1 * 180.0/math.pi
|
||||
pp2deg = pp2 * 180.0/math.pi
|
||||
|
||||
|
||||
n_src = 1
|
||||
n_rec = [60 for x in range(n_src)]
|
||||
|
||||
|
||||
lines = []
|
||||
|
||||
nij_src = math.sqrt(n_src)
|
||||
nij_rec = math.sqrt(n_rec[0])
|
||||
|
||||
pos_src=[]
|
||||
pos_rec=[]
|
||||
|
||||
# create dummy src
|
||||
for i_src in range(n_src):
|
||||
# define one point in the domain (rr1 bottom, rr2 top)
|
||||
# random
|
||||
#dep = random.uniform((R_earth-rr1)*0.95,(R_earth-rr1)*0.98)
|
||||
#lon = random.uniform(pp1deg,pp2deg)
|
||||
#lat = random.uniform(tt1deg,tt2deg)
|
||||
# regularl
|
||||
dep = (R_earth-rr1)*0.9
|
||||
tmp_ilon = i_src%nij_src
|
||||
tmp_ilat = int(i_src/nij_src)
|
||||
lon = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_src
|
||||
lat = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_src
|
||||
|
||||
src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]
|
||||
lines.append(src)
|
||||
|
||||
pos_src.append([lon,lat,dep])
|
||||
|
||||
|
||||
# create dummy station
|
||||
for i_rec in range(n_rec[i_src]):
|
||||
#elev_rec = random.uniform(0.0,-10.0) # elevation in m
|
||||
#lon_rec = random.uniform(pp1deg,pp2deg)
|
||||
#lat_rec = random.uniform(tt1deg,tt2deg)
|
||||
# regularly
|
||||
elev_rec = -10.0
|
||||
tmp_ilon = i_rec%nij_rec
|
||||
tmp_ilat = int(i_rec/nij_rec)
|
||||
lon_rec = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec
|
||||
lat_rec = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec
|
||||
|
||||
rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]
|
||||
lines.append(rec)
|
||||
|
||||
pos_rec.append([lon_rec,lat_rec,elev_rec])
|
||||
|
||||
|
||||
# write out ev_arrivals file
|
||||
fname = 'src_rec_test.dat'
|
||||
|
||||
with open(fname, 'w') as f:
|
||||
for line in lines:
|
||||
for elem in line:
|
||||
f.write('{} '.format(elem))
|
||||
f.write('\n')
|
||||
|
||||
|
||||
# %%
|
||||
# draw src and rec positions
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
for i_src in range(n_src):
|
||||
plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
|
||||
|
||||
# %%
|
||||
# plot receivers
|
||||
for i_rec in range(n_rec[0]):
|
||||
plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
|
||||
|
||||
# %%
|
||||
|
||||
|
||||
|
||||
136
test/old_tests/inversion_tele/1d_ak135.txt
Normal file
136
test/old_tests/inversion_tele/1d_ak135.txt
Normal file
@@ -0,0 +1,136 @@
|
||||
0.000, 5.8000
|
||||
20.000, 5.8000
|
||||
20.000, 6.5000
|
||||
35.000, 6.5000
|
||||
35.000, 8.0400
|
||||
77.500, 8.0450
|
||||
120.000, 8.0500
|
||||
165.000, 8.1750
|
||||
210.000, 8.3000
|
||||
210.000, 8.3000
|
||||
260.000, 8.4825
|
||||
310.000, 8.6650
|
||||
360.000, 8.8475
|
||||
410.000, 9.0300
|
||||
410.000, 9.3600
|
||||
460.000, 9.5280
|
||||
510.000, 9.6960
|
||||
560.000, 9.8640
|
||||
610.000, 10.0320
|
||||
660.000, 10.2000
|
||||
660.000, 10.7900
|
||||
710.000, 10.9229
|
||||
760.000, 11.0558
|
||||
809.500, 11.1353
|
||||
859.000, 11.2221
|
||||
908.500, 11.3068
|
||||
958.000, 11.3896
|
||||
1007.500, 11.4705
|
||||
1057.000, 11.5495
|
||||
1106.500, 11.6269
|
||||
1156.000, 11.7026
|
||||
1205.500, 11.7766
|
||||
1255.000, 11.8491
|
||||
1304.500, 11.9200
|
||||
1354.000, 11.9895
|
||||
1403.500, 12.0577
|
||||
1453.000, 12.1245
|
||||
1502.500, 12.1912
|
||||
1552.000, 12.2550
|
||||
1601.500, 12.3185
|
||||
1651.000, 12.3819
|
||||
1700.500, 12.4426
|
||||
1750.000, 12.5031
|
||||
1799.500, 12.5631
|
||||
1849.000, 12.6221
|
||||
1898.500, 12.6804
|
||||
1948.000, 12.7382
|
||||
1997.500, 12.7956
|
||||
2047.000, 12.8526
|
||||
2096.500, 12.9096
|
||||
2146.000, 12.9668
|
||||
2195.500, 13.0222
|
||||
2245.000, 13.0783
|
||||
2294.500, 13.1336
|
||||
2344.000, 13.1894
|
||||
2393.500, 13.2465
|
||||
2443.000, 13.3018
|
||||
2492.500, 13.3585
|
||||
2542.000, 13.4156
|
||||
2591.500, 13.4741
|
||||
2640.000, 13.5312
|
||||
2690.000, 13.5900
|
||||
2740.000, 13.6494
|
||||
2740.000, 13.6494
|
||||
2789.670, 13.6530
|
||||
2839.330, 13.6566
|
||||
2891.500, 13.6602
|
||||
2891.500, 8.0000
|
||||
2939.330, 8.0382
|
||||
2989.660, 8.1283
|
||||
3039.990, 8.2213
|
||||
3090.320, 8.3122
|
||||
3140.660, 8.4001
|
||||
3190.990, 8.4861
|
||||
3241.320, 8.5692
|
||||
3291.650, 8.6496
|
||||
3341.980, 8.7283
|
||||
3392.310, 8.8036
|
||||
3442.640, 8.8761
|
||||
3492.970, 8.9461
|
||||
3543.300, 9.0138
|
||||
3593.640, 9.0792
|
||||
3643.970, 9.1426
|
||||
3694.300, 9.2042
|
||||
3744.630, 9.2634
|
||||
3794.960, 9.3205
|
||||
3845.290, 9.3760
|
||||
3895.620, 9.4297
|
||||
3945.950, 9.4814
|
||||
3996.280, 9.5306
|
||||
4046.620, 9.5777
|
||||
4096.950, 9.6232
|
||||
4147.280, 9.6673
|
||||
4197.610, 9.7100
|
||||
4247.940, 9.7513
|
||||
4298.270, 9.7914
|
||||
4348.600, 9.8304
|
||||
4398.930, 9.8682
|
||||
4449.260, 9.9051
|
||||
4499.600, 9.9410
|
||||
4549.930, 9.9761
|
||||
4600.260, 10.0103
|
||||
4650.590, 10.0439
|
||||
4700.920, 10.0768
|
||||
4801.580, 10.1415
|
||||
4851.910, 10.1739
|
||||
4902.240, 10.2049
|
||||
4952.580, 10.2329
|
||||
5002.910, 10.2565
|
||||
5053.240, 10.2745
|
||||
5103.570, 10.2854
|
||||
5153.500, 10.2890
|
||||
5153.500, 11.0427
|
||||
5204.610, 11.0585
|
||||
5255.320, 11.0718
|
||||
5306.040, 11.0850
|
||||
5356.750, 11.0983
|
||||
5407.460, 11.1166
|
||||
5458.170, 11.1316
|
||||
5508.890, 11.1457
|
||||
5559.600, 11.1590
|
||||
5610.310, 11.1715
|
||||
5661.020, 11.1832
|
||||
5711.740, 11.1941
|
||||
5813.160, 11.2134
|
||||
5863.870, 11.2219
|
||||
5914.590, 11.2295
|
||||
5965.300, 11.2364
|
||||
6016.010, 11.2424
|
||||
6066.720, 11.2477
|
||||
6117.440, 11.2521
|
||||
6168.150, 11.2557
|
||||
6218.860, 11.2586
|
||||
6269.570, 11.2606
|
||||
6320.290, 11.2618
|
||||
6371.000, 11.2622
|
||||
158
test/old_tests/inversion_tele/1d_model.txt
Normal file
158
test/old_tests/inversion_tele/1d_model.txt
Normal file
@@ -0,0 +1,158 @@
|
||||
5463, 11.3059
|
||||
5473, 11.2888
|
||||
5483, 11.2717
|
||||
5493, 11.2546
|
||||
5503, 11.2375
|
||||
5513, 11.2203
|
||||
5523, 11.2028
|
||||
5533, 11.1853
|
||||
5543, 11.1677
|
||||
5553, 11.1502
|
||||
5563, 11.1329
|
||||
5573, 11.1168
|
||||
5583, 11.1008
|
||||
5593, 11.0847
|
||||
5603, 11.0686
|
||||
5613, 11.0505
|
||||
5623, 11.0239
|
||||
5633, 10.9973
|
||||
5643, 10.9707
|
||||
5653, 10.9442
|
||||
5663, 10.9176
|
||||
5673, 10.891
|
||||
5683, 10.8644
|
||||
5693, 10.8378
|
||||
5703, 10.8113
|
||||
5713, 10.1933
|
||||
5723, 10.1597
|
||||
5733, 10.1261
|
||||
5743, 10.0925
|
||||
5753, 10.0589
|
||||
5763, 10.0253
|
||||
5773, 9.99168
|
||||
5783, 9.95808
|
||||
5793, 9.92448
|
||||
5803, 9.89088
|
||||
5813, 9.85728
|
||||
5823, 9.82368
|
||||
5833, 9.79008
|
||||
5843, 9.75648
|
||||
5853, 9.72288
|
||||
5863, 9.68928
|
||||
5873, 9.65568
|
||||
5883, 9.62208
|
||||
5893, 9.58848
|
||||
5903, 9.55488
|
||||
5913, 9.52128
|
||||
5923, 9.48768
|
||||
5933, 9.45408
|
||||
5943, 9.42048
|
||||
5953, 9.38688
|
||||
5963, 9.0227
|
||||
5973, 8.9862
|
||||
5983, 8.9497
|
||||
5993, 8.9132
|
||||
6003, 8.8767
|
||||
6013, 8.8402
|
||||
6023, 8.8037
|
||||
6033, 8.7672
|
||||
6043, 8.7307
|
||||
6053, 8.6942
|
||||
6063, 8.6577
|
||||
6073, 8.6212
|
||||
6083, 8.5847
|
||||
6093, 8.5482
|
||||
6103, 8.5117
|
||||
6113, 8.4752
|
||||
6123, 8.4387
|
||||
6133, 8.4022
|
||||
6143, 8.3657
|
||||
6153, 8.3292
|
||||
6163, 8.29444
|
||||
6173, 8.26667
|
||||
6183, 8.23889
|
||||
6193, 8.21111
|
||||
6203, 8.18333
|
||||
6213, 8.15556
|
||||
6223, 8.12778
|
||||
6233, 8.1
|
||||
6243, 8.07222
|
||||
6253, 8.04976
|
||||
6263, 8.04859
|
||||
6273, 8.04741
|
||||
6283, 8.04624
|
||||
6293, 8.04506
|
||||
6303, 8.04388
|
||||
6313, 8.04271
|
||||
6323, 8.04153
|
||||
6333, 8.04035
|
||||
6343, 6.5
|
||||
6353, 5.8
|
||||
6363, 5.8
|
||||
6373, 5.8
|
||||
6383, 5.8
|
||||
6393, 5.8
|
||||
6403, 5.8
|
||||
6413, 5.8
|
||||
6423, 5.8
|
||||
6433, 5.8
|
||||
6443, 5.8
|
||||
6453, 5.8
|
||||
6463, 5.8
|
||||
6473, 5.8
|
||||
6483, 5.8
|
||||
6493, 5.8
|
||||
6503, 5.8
|
||||
6513, 5.8
|
||||
6523, 5.8
|
||||
6533, 5.8
|
||||
6543, 5.8
|
||||
6553, 5.8
|
||||
6563, 5.8
|
||||
6573, 5.8
|
||||
6583, 5.8
|
||||
6593, 5.8
|
||||
6603, 5.8
|
||||
6613, 5.8
|
||||
6623, 5.8
|
||||
6633, 5.8
|
||||
6643, 5.8
|
||||
6653, 5.8
|
||||
6663, 5.8
|
||||
6673, 5.8
|
||||
6683, 5.8
|
||||
6693, 5.8
|
||||
6703, 5.8
|
||||
6713, 5.8
|
||||
6723, 5.8
|
||||
6733, 5.8
|
||||
6743, 5.8
|
||||
6753, 5.8
|
||||
6763, 5.8
|
||||
6773, 5.8
|
||||
6783, 5.8
|
||||
6793, 5.8
|
||||
6803, 5.8
|
||||
6813, 5.8
|
||||
6823, 5.8
|
||||
6833, 5.8
|
||||
6843, 5.8
|
||||
6853, 5.8
|
||||
6863, 5.8
|
||||
6873, 5.8
|
||||
6883, 5.8
|
||||
6893, 5.8
|
||||
6903, 5.8
|
||||
6913, 5.8
|
||||
6923, 5.8
|
||||
6933, 5.8
|
||||
6943, 5.8
|
||||
6953, 5.8
|
||||
6963, 5.8
|
||||
6973, 5.8
|
||||
6983, 5.8
|
||||
6993, 5.8
|
||||
7003, 5.8
|
||||
7013, 5.8
|
||||
7023, 5.8
|
||||
7033, 5.8
|
||||
30
test/old_tests/inversion_tele/README.md
Normal file
30
test/old_tests/inversion_tele/README.md
Normal file
@@ -0,0 +1,30 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation with teleseismic events.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` for creating
|
||||
- source, receiver file (src_rec_test.dat)
|
||||
- true model (test_model_true.h5)
|
||||
- initial model (test_model_init.h5)
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
At first, TOMOATT calculates 2d traveltime field for each teleseismic event.
|
||||
TOMOATT will find the event source is teleseismic if the event origin is outside of the simulation domain.
|
||||
Calculated 2d traveltime field is saved in OUTPUT_FILES directory with 2d_travel_time_field_{src_id}.h5
|
||||
2D solver run will be skipped if this file is found by TOMOATT.
|
||||
Result travel time at the stations is saved in the file `src_rec_test_out.dat`
|
||||
Following command will run the forward simulation with the true model
|
||||
``` bash
|
||||
mpirun -n 8 ../../build/TOMOATT -i input_params_pre.yml
|
||||
```
|
||||
Volumetric output data is saved in the file `OUTPUT_FILES/out_data_sim_0.h5`.
|
||||
This file may be visualized by paraview with opening the index file `OUTPUT_FILES/out_data_sim_0.xmf`.
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`, by the command
|
||||
``` bash
|
||||
mpirun -n 8 ../../build/TOMOATT -i input_params.yml
|
||||
```
|
||||
The volumetric output data is saved in the file `OUTPUT_FILES/out_data_sim_0.h5`.
|
||||
|
||||
|
||||
4. For retrieving the output data from *.h5, please use the python script `utils/tomoatt_data_retrieval.py`
|
||||
111
test/old_tests/inversion_tele/check_1d_model_and_Tfield.ipynb
Normal file
111
test/old_tests/inversion_tele/check_1d_model_and_Tfield.ipynb
Normal file
@@ -0,0 +1,111 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot 1d_model.txt\n",
|
||||
"fname_gen='1d_model.txt'\n",
|
||||
"fname_ori='1d_ak135.txt'\n",
|
||||
"\n",
|
||||
"r_earth = 6371.0\n",
|
||||
"\n",
|
||||
"# read file\n",
|
||||
"\n",
|
||||
"dep_gen=[]\n",
|
||||
"vp_gen=[]\n",
|
||||
"\n",
|
||||
"with open(fname_gen, 'r') as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" for line in lines:\n",
|
||||
" line = line.strip()\n",
|
||||
" if line.startswith('#'):\n",
|
||||
" continue\n",
|
||||
" else:\n",
|
||||
" line = line.split(\",\")\n",
|
||||
" dep_gen.append(r_earth-float(line[0]))\n",
|
||||
" vp_gen.append(float(line[1]))\n",
|
||||
"\n",
|
||||
"dep_ori=[]\n",
|
||||
"vp_ori=[]\n",
|
||||
"\n",
|
||||
"with open(fname_ori,'r') as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" for line in lines:\n",
|
||||
" line = line.strip()\n",
|
||||
" if line.startswith('#'):\n",
|
||||
" continue\n",
|
||||
" else:\n",
|
||||
" line = line.split(\",\")\n",
|
||||
" dep_ori.append(float(line[0]))\n",
|
||||
" vp_ori.append(float(line[1]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# plot dep and vp\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"plt.plot(dep_gen, vp_gen, linewidth=10)\n",
|
||||
"plt.plot(dep_ori, vp_ori)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# read 2D traveltime field and plot\n",
|
||||
"import h5py\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"fname_Tfield='OUTPUT_FILES/2d_travel_time_field_0.h5'\n",
|
||||
"\n",
|
||||
"with h5py.File(fname_Tfield, 'r') as f:\n",
|
||||
" T_2d = f['T'][:,:]\n",
|
||||
" t_1d = f['t'][:]\n",
|
||||
" r_1d = f['r'][:]\n",
|
||||
"\n",
|
||||
"plt.imshow(T_2d, extent=[t_1d[0], t_1d[-1], r_1d[0], r_1d[-1]], aspect='auto') \n",
|
||||
"plt.colorbar()\n",
|
||||
"#plt.imshow(T_2d)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -0,0 +1,201 @@
|
||||
200
|
||||
11.802 0.000 120.430
|
||||
10.977 0.000 112.347
|
||||
14.799 0.000 116.441
|
||||
13.870 0.000 114.593
|
||||
2.238 0.000 118.621
|
||||
18.077 0.000 111.279
|
||||
15.485 0.000 128.750
|
||||
5.138 0.000 129.964
|
||||
1.021 0.000 117.016
|
||||
16.461 0.000 124.992
|
||||
12.131 0.000 127.582
|
||||
1.691 0.000 129.371
|
||||
14.213 0.000 120.983
|
||||
12.474 0.000 125.122
|
||||
10.740 0.000 129.356
|
||||
15.138 0.000 119.121
|
||||
16.849 0.000 113.748
|
||||
10.421 0.000 127.899
|
||||
8.083 0.000 113.566
|
||||
7.194 0.000 127.568
|
||||
15.695 0.000 129.820
|
||||
15.755 0.000 128.741
|
||||
4.287 0.000 119.474
|
||||
3.368 0.000 116.248
|
||||
16.400 0.000 110.836
|
||||
2.200 0.000 126.318
|
||||
8.136 0.000 128.447
|
||||
14.206 0.000 127.036
|
||||
11.432 0.000 126.942
|
||||
8.027 0.000 118.581
|
||||
2.233 0.000 126.321
|
||||
2.856 0.000 128.286
|
||||
15.194 0.000 111.542
|
||||
19.468 0.000 114.427
|
||||
18.235 0.000 116.594
|
||||
11.378 0.000 117.484
|
||||
7.172 0.000 113.442
|
||||
15.956 0.000 125.590
|
||||
2.810 0.000 114.026
|
||||
12.895 0.000 127.486
|
||||
8.131 0.000 125.399
|
||||
9.603 0.000 127.463
|
||||
9.059 0.000 127.470
|
||||
15.437 0.000 117.213
|
||||
4.344 0.000 120.949
|
||||
8.399 0.000 112.079
|
||||
6.747 0.000 114.103
|
||||
8.264 0.000 119.535
|
||||
8.660 0.000 125.041
|
||||
12.518 0.000 111.975
|
||||
1.344 0.000 115.458
|
||||
14.245 0.000 122.863
|
||||
14.446 0.000 127.582
|
||||
7.296 0.000 123.609
|
||||
15.986 0.000 118.914
|
||||
2.741 0.000 128.433
|
||||
2.776 0.000 114.310
|
||||
10.058 0.000 118.660
|
||||
4.767 0.000 112.640
|
||||
6.614 0.000 123.114
|
||||
18.459 0.000 128.929
|
||||
5.942 0.000 112.869
|
||||
9.770 0.000 123.277
|
||||
11.403 0.000 128.818
|
||||
10.440 0.000 127.002
|
||||
11.587 0.000 122.665
|
||||
13.228 0.000 127.416
|
||||
2.504 0.000 110.861
|
||||
3.837 0.000 120.637
|
||||
15.225 0.000 112.534
|
||||
12.590 0.000 123.332
|
||||
9.117 0.000 122.897
|
||||
15.230 0.000 125.084
|
||||
6.218 0.000 129.723
|
||||
17.309 0.000 125.024
|
||||
2.178 0.000 120.731
|
||||
13.611 0.000 112.946
|
||||
2.805 0.000 123.454
|
||||
4.944 0.000 115.870
|
||||
14.004 0.000 125.492
|
||||
4.209 0.000 125.665
|
||||
13.779 0.000 123.429
|
||||
2.183 0.000 118.440
|
||||
5.357 0.000 123.154
|
||||
13.240 0.000 116.284
|
||||
18.648 0.000 121.295
|
||||
19.219 0.000 115.919
|
||||
1.486 0.000 121.474
|
||||
2.457 0.000 119.333
|
||||
16.288 0.000 127.138
|
||||
5.268 0.000 121.570
|
||||
5.623 0.000 122.193
|
||||
12.494 0.000 112.512
|
||||
1.649 0.000 120.953
|
||||
18.253 0.000 113.672
|
||||
4.109 0.000 115.474
|
||||
15.850 0.000 121.814
|
||||
6.920 0.000 115.925
|
||||
3.525 0.000 127.491
|
||||
7.125 0.000 127.679
|
||||
8.291 0.000 129.702
|
||||
2.453 0.000 116.388
|
||||
10.126 0.000 114.561
|
||||
16.671 0.000 115.128
|
||||
9.499 0.000 115.955
|
||||
7.057 0.000 114.557
|
||||
9.537 0.000 118.136
|
||||
17.129 0.000 127.229
|
||||
13.159 0.000 123.202
|
||||
18.156 0.000 112.430
|
||||
12.148 0.000 127.744
|
||||
4.707 0.000 118.976
|
||||
12.066 0.000 113.261
|
||||
9.917 0.000 112.249
|
||||
4.562 0.000 115.574
|
||||
9.033 0.000 111.773
|
||||
2.664 0.000 115.781
|
||||
3.620 0.000 113.157
|
||||
8.536 0.000 124.149
|
||||
12.984 0.000 118.287
|
||||
11.377 0.000 114.723
|
||||
14.438 0.000 117.563
|
||||
6.770 0.000 117.346
|
||||
19.103 0.000 122.253
|
||||
11.890 0.000 120.057
|
||||
1.882 0.000 125.606
|
||||
6.826 0.000 120.949
|
||||
1.447 0.000 124.624
|
||||
11.237 0.000 114.481
|
||||
18.727 0.000 124.695
|
||||
16.117 0.000 125.042
|
||||
9.385 0.000 111.953
|
||||
2.156 0.000 110.976
|
||||
17.274 0.000 110.739
|
||||
11.901 0.000 116.806
|
||||
3.311 0.000 112.308
|
||||
16.118 0.000 129.010
|
||||
14.839 0.000 111.311
|
||||
14.383 0.000 114.445
|
||||
4.545 0.000 110.627
|
||||
6.887 0.000 111.142
|
||||
15.771 0.000 129.508
|
||||
16.464 0.000 111.184
|
||||
5.103 0.000 113.133
|
||||
5.517 0.000 111.094
|
||||
11.793 0.000 121.722
|
||||
9.895 0.000 127.312
|
||||
2.327 0.000 117.660
|
||||
9.218 0.000 127.343
|
||||
17.444 0.000 120.635
|
||||
13.747 0.000 115.551
|
||||
14.244 0.000 112.432
|
||||
7.793 0.000 123.270
|
||||
2.825 0.000 128.950
|
||||
17.617 0.000 127.288
|
||||
2.807 0.000 126.756
|
||||
15.653 0.000 126.819
|
||||
17.047 0.000 120.984
|
||||
5.550 0.000 128.964
|
||||
18.377 0.000 111.008
|
||||
9.899 0.000 124.873
|
||||
17.878 0.000 126.725
|
||||
9.937 0.000 121.221
|
||||
9.665 0.000 127.646
|
||||
11.705 0.000 118.606
|
||||
8.598 0.000 123.095
|
||||
9.381 0.000 112.372
|
||||
12.011 0.000 111.390
|
||||
9.745 0.000 126.383
|
||||
6.575 0.000 112.135
|
||||
1.758 0.000 125.892
|
||||
14.843 0.000 114.231
|
||||
2.378 0.000 115.137
|
||||
13.871 0.000 121.657
|
||||
17.999 0.000 127.665
|
||||
11.245 0.000 120.451
|
||||
2.764 0.000 112.762
|
||||
15.920 0.000 111.560
|
||||
12.590 0.000 115.623
|
||||
10.907 0.000 128.019
|
||||
14.613 0.000 125.835
|
||||
11.296 0.000 120.752
|
||||
5.326 0.000 115.745
|
||||
8.918 0.000 125.743
|
||||
14.636 0.000 122.201
|
||||
10.490 0.000 126.751
|
||||
13.210 0.000 129.310
|
||||
14.389 0.000 122.314
|
||||
10.010 0.000 112.866
|
||||
2.412 0.000 122.699
|
||||
10.634 0.000 129.658
|
||||
15.328 0.000 116.282
|
||||
17.949 0.000 117.036
|
||||
10.058 0.000 129.116
|
||||
10.862 0.000 126.679
|
||||
5.712 0.000 113.093
|
||||
7.001 0.000 119.322
|
||||
17.848 0.000 129.814
|
||||
2.726 0.000 123.738
|
||||
2.228 0.000 123.016
|
||||
@@ -0,0 +1,31 @@
|
||||
30
|
||||
93.754 0.000 167.742 90.000 47.742
|
||||
91.741 0.000 76.894 270.000 43.106
|
||||
28.520 0.000 192.245 90.000 72.245
|
||||
99.877 0.000 171.239 90.000 51.239
|
||||
29.960 0.000 68.069 270.000 51.931
|
||||
63.202 0.000 57.747 270.000 62.253
|
||||
25.908 0.000 199.894 90.000 79.894
|
||||
60.869 0.000 72.681 270.000 47.319
|
||||
58.767 0.000 77.051 270.000 42.949
|
||||
12.108 0.000 189.167 90.000 69.167
|
||||
46.008 0.000 43.608 270.000 76.392
|
||||
10.170 0.000 74.481 270.000 45.519
|
||||
89.800 0.000 175.250 90.000 55.250
|
||||
31.693 0.000 166.363 90.000 46.363
|
||||
93.750 0.000 68.855 270.000 51.145
|
||||
51.260 0.000 193.542 90.000 73.542
|
||||
86.110 0.000 172.078 90.000 52.078
|
||||
10.661 0.000 191.059 90.000 71.059
|
||||
22.843 0.000 56.609 270.000 63.391
|
||||
61.437 0.000 176.890 90.000 56.890
|
||||
62.972 0.000 58.230 270.000 61.770
|
||||
39.053 0.000 185.517 90.000 65.517
|
||||
32.690 0.000 167.737 90.000 47.737
|
||||
78.764 0.000 190.265 90.000 70.265
|
||||
76.323 0.000 184.958 90.000 64.958
|
||||
33.802 0.000 47.777 270.000 72.223
|
||||
25.489 0.000 62.227 270.000 57.773
|
||||
51.580 0.000 195.428 90.000 75.428
|
||||
64.127 0.000 171.087 90.000 51.087
|
||||
92.574 0.000 73.692 270.000 46.308
|
||||
@@ -0,0 +1,41 @@
|
||||
40
|
||||
0.000 0.000 110.250
|
||||
0.000 0.000 110.750
|
||||
0.000 0.000 111.250
|
||||
0.000 0.000 111.750
|
||||
0.000 0.000 112.250
|
||||
0.000 0.000 112.750
|
||||
0.000 0.000 113.250
|
||||
0.000 0.000 113.750
|
||||
0.000 0.000 114.250
|
||||
0.000 0.000 114.750
|
||||
0.000 0.000 115.250
|
||||
0.000 0.000 115.750
|
||||
0.000 0.000 116.250
|
||||
0.000 0.000 116.750
|
||||
0.000 0.000 117.250
|
||||
0.000 0.000 117.750
|
||||
0.000 0.000 118.250
|
||||
0.000 0.000 118.750
|
||||
0.000 0.000 119.250
|
||||
0.000 0.000 119.750
|
||||
0.000 0.000 120.250
|
||||
0.000 0.000 120.750
|
||||
0.000 0.000 121.250
|
||||
0.000 0.000 121.750
|
||||
0.000 0.000 122.250
|
||||
0.000 0.000 122.750
|
||||
0.000 0.000 123.250
|
||||
0.000 0.000 123.750
|
||||
0.000 0.000 124.250
|
||||
0.000 0.000 124.750
|
||||
0.000 0.000 125.250
|
||||
0.000 0.000 125.750
|
||||
0.000 0.000 126.250
|
||||
0.000 0.000 126.750
|
||||
0.000 0.000 127.250
|
||||
0.000 0.000 127.750
|
||||
0.000 0.000 128.250
|
||||
0.000 0.000 128.750
|
||||
0.000 0.000 129.250
|
||||
0.000 0.000 129.750
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,89 @@
|
||||
88
|
||||
0.00 5.80000 3.20000 2.60000 1456.0 600.0
|
||||
15.00 5.80000 3.20000 2.60000 1456.0 600.0
|
||||
15.00 6.80000 3.90000 2.90000 1350.0 600.0
|
||||
24.40 6.80000 3.90000 2.90000 1350.0 600.0
|
||||
24.40 8.11061 4.49094 3.38076 1446.0 600.0
|
||||
40.00 8.10119 4.48486 3.37906 1446.0 600.0
|
||||
60.00 8.08907 4.47715 3.37688 1447.0 600.0
|
||||
80.00 8.07688 4.46953 3.37471 195.0 80.0
|
||||
115.00 8.05540 4.45643 3.37091 195.0 80.0
|
||||
150.00 8.03370 4.44361 3.36710 195.0 80.0
|
||||
185.00 8.01180 4.43108 3.36330 195.0 80.0
|
||||
220.00 7.98970 4.41885 3.35950 195.0 80.0
|
||||
220.00 8.55896 4.64391 3.43578 362.0 143.0
|
||||
265.00 8.64552 4.67540 3.46264 365.0 143.0
|
||||
310.00 8.73209 4.70690 3.48951 367.0 143.0
|
||||
355.00 8.81867 4.73840 3.51639 370.0 143.0
|
||||
400.00 8.90522 4.76989 3.54325 372.0 143.0
|
||||
400.00 9.13397 4.93259 3.72378 366.0 143.0
|
||||
450.00 9.38990 5.07842 3.78678 365.0 143.0
|
||||
500.00 9.64588 5.22428 3.84980 364.0 143.0
|
||||
550.00 9.90185 5.37014 3.91282 363.0 143.0
|
||||
600.00 10.15782 5.51602 3.97584 362.0 143.0
|
||||
635.00 10.21203 5.54311 3.98399 362.0 143.0
|
||||
670.00 10.26622 5.57020 3.99214 362.0 143.0
|
||||
670.00 10.75131 5.94508 4.38071 759.0 312.0
|
||||
721.00 10.91005 6.09418 4.41241 744.0 312.0
|
||||
771.00 11.06557 6.24046 4.44317 730.0 312.0
|
||||
871.00 11.24490 6.31091 4.50372 737.0 312.0
|
||||
971.00 11.41560 6.37813 4.56307 743.0 312.0
|
||||
1071.00 11.57828 6.44232 4.62129 750.0 312.0
|
||||
1171.00 11.73357 6.50370 4.67844 755.0 312.0
|
||||
1271.00 11.88209 6.56250 4.73460 761.0 312.0
|
||||
1371.00 12.02445 6.61891 4.78983 766.0 312.0
|
||||
1471.00 12.16126 6.67317 4.84422 770.0 312.0
|
||||
1571.00 12.29316 6.72548 4.89783 775.0 312.0
|
||||
1671.00 12.42075 6.77606 4.95073 779.0 312.0
|
||||
1771.00 12.54466 6.82512 5.00299 784.0 312.0
|
||||
1871.00 12.66550 6.87289 5.05469 788.0 312.0
|
||||
1971.00 12.78389 6.91957 5.10590 792.0 312.0
|
||||
2071.00 12.90045 6.96538 5.15669 795.0 312.0
|
||||
2171.00 13.01579 7.01053 5.20713 799.0 312.0
|
||||
2271.00 13.13055 7.05525 5.25729 803.0 312.0
|
||||
2371.00 13.24532 7.09974 5.30724 807.0 312.0
|
||||
2471.00 13.36074 7.14423 5.35706 811.0 312.0
|
||||
2571.00 13.47742 7.18892 5.40681 815.0 312.0
|
||||
2671.00 13.59597 7.23403 5.45657 819.0 312.0
|
||||
2741.00 13.68041 7.26597 5.49145 822.0 312.0
|
||||
2771.00 13.68753 7.26575 5.50642 823.0 312.0
|
||||
2871.00 13.71168 7.26486 5.55641 826.0 312.0
|
||||
2891.00 13.71660 7.26466 5.56645 826.0 312.0
|
||||
2891.00 8.06482 0.00000 9.90349 57822.0 0.0
|
||||
2971.00 8.19939 0.00000 10.02940 57822.0 0.0
|
||||
3071.00 8.36019 0.00000 10.18134 57822.0 0.0
|
||||
3171.00 8.51298 0.00000 10.32726 57822.0 0.0
|
||||
3271.00 8.65805 0.00000 10.46727 57822.0 0.0
|
||||
3371.00 8.79573 0.00000 10.60152 57822.0 0.0
|
||||
3471.00 8.92632 0.00000 10.73012 57822.0 0.0
|
||||
3571.00 9.05015 0.00000 10.85321 57822.0 0.0
|
||||
3671.00 9.16752 0.00000 10.97091 57822.0 0.0
|
||||
3771.00 9.27867 0.00000 11.08335 57822.0 0.0
|
||||
3871.00 9.38418 0.00000 11.19067 57822.0 0.0
|
||||
3971.00 9.48409 0.00000 11.29298 57822.0 0.0
|
||||
4071.00 9.57881 0.00000 11.39042 57822.0 0.0
|
||||
4171.00 9.66865 0.00000 11.48311 57822.0 0.0
|
||||
4271.00 9.75393 0.00000 11.57119 57822.0 0.0
|
||||
4371.00 9.83496 0.00000 11.65478 57822.0 0.0
|
||||
4471.00 9.91206 0.00000 11.73401 57822.0 0.0
|
||||
4571.00 9.98554 0.00000 11.80900 57822.0 0.0
|
||||
4671.00 10.05572 0.00000 11.87990 57822.0 0.0
|
||||
4771.00 10.12291 0.00000 11.94682 57822.0 0.0
|
||||
4871.00 10.18743 0.00000 12.00989 57822.0 0.0
|
||||
4971.00 10.24959 0.00000 12.06924 57822.0 0.0
|
||||
5071.00 10.30971 0.00000 12.12500 57822.0 0.0
|
||||
5149.50 10.35568 0.00000 12.16634 57822.0 0.0
|
||||
5149.50 11.02827 3.50432 12.76360 445.0 85.0
|
||||
5171.00 11.03643 3.51002 12.77493 445.0 85.0
|
||||
5271.00 11.07249 3.53522 12.82501 443.0 85.0
|
||||
5371.00 11.10542 3.55823 12.87073 440.0 85.0
|
||||
5471.00 11.13521 3.57905 12.91211 439.0 85.0
|
||||
5571.00 11.16186 3.59767 12.94912 437.0 85.0
|
||||
5671.00 11.18538 3.61411 12.98178 436.0 85.0
|
||||
5771.00 11.20576 3.62835 13.01009 434.0 85.0
|
||||
5871.00 11.22301 3.64041 13.03404 433.0 85.0
|
||||
5971.00 11.23712 3.65027 13.05364 432.0 85.0
|
||||
6071.00 11.24809 3.65794 13.06888 432.0 85.0
|
||||
6171.00 11.25593 3.66342 13.07977 431.0 85.0
|
||||
6271.00 11.26064 3.66670 13.08630 431.0 85.0
|
||||
6371.00 11.26220 3.66780 13.08848 431.0 85.0
|
||||
1016
test/old_tests/inversion_tele/fortran_code/ega5_sphe_3d_kernel.f90
Normal file
1016
test/old_tests/inversion_tele/fortran_code/ega5_sphe_3d_kernel.f90
Normal file
File diff suppressed because it is too large
Load Diff
5333
test/old_tests/inversion_tele/fortran_code/eikon_solver_mpi.f90
Normal file
5333
test/old_tests/inversion_tele/fortran_code/eikon_solver_mpi.f90
Normal file
File diff suppressed because it is too large
Load Diff
48
test/old_tests/inversion_tele/input_params.yml
Normal file
48
test/old_tests/inversion_tele/input_params.yml
Normal file
@@ -0,0 +1,48 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test_out.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
optim_method : 2 # optimization method. 0 : "grad_descent", 1 : "lbfgs", 2 : "halve-stepping"
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [11,10,10] # number of the base inversion grid points
|
||||
#min_max_dep_inv : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
#min_max_lat_inv : [30.0,50.0] # latitude in degree
|
||||
#min_max_lon_inv : [15.0,40.0] # longitude in degree
|
||||
max_sub_iterations : 100 # maximum number of sub-iterations
|
||||
#smooth_method : 1 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
#l_smooth_rtp : [0.9,0.9,0.9] # smoothing coefficients for each direction
|
||||
|
||||
max_iterations_inv : 100 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,4] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
use_gpu : 0
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-3
|
||||
max_iterations : 100
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
36
test/old_tests/inversion_tele/input_params_pre.yml
Normal file
36
test/old_tests/inversion_tele/input_params_pre.yml
Normal file
@@ -0,0 +1,36 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [2,2,2] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 100
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 2 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
|
||||
352
test/old_tests/inversion_tele/make_test_model.ipynb
Normal file
352
test/old_tests/inversion_tele/make_test_model.ipynb
Normal file
@@ -0,0 +1,352 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"R_earth = 6371.0 #6378.1370\n",
|
||||
"\n",
|
||||
"rr1=6070\n",
|
||||
"rr2=6400\n",
|
||||
"tt1=(30.0-1.5)/180*math.pi\n",
|
||||
"tt2=(50.0+1.5)/180*math.pi\n",
|
||||
"pp1=(15.0-1.5)/180*math.pi\n",
|
||||
"pp2=(40.0+1.5)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [55,55,55]\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[0]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[2]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"#s0 = 1.0/6.0\n",
|
||||
"slow_p=0.04\n",
|
||||
"ani_p=0.03\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"a_init = np.zeros(n_rtp)\n",
|
||||
"b_init = np.zeros(n_rtp)\n",
|
||||
"c_init = np.zeros(n_rtp)\n",
|
||||
"f_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"a_true = np.zeros(n_rtp)\n",
|
||||
"b_true = np.zeros(n_rtp)\n",
|
||||
"c_true = np.zeros(n_rtp)\n",
|
||||
"f_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ir,it,ip] = 0.0\n",
|
||||
" #xi_init[ir,it,ip] = 0.0\n",
|
||||
" zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)\n",
|
||||
" \n",
|
||||
" if (rr[ir]>6351):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)\n",
|
||||
" elif (rr[ir]>6336):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)\n",
|
||||
" elif (rr[ir]>5961):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1) \n",
|
||||
" else:\n",
|
||||
" fun_init[ir,it,ip] = 1.0/9.0\n",
|
||||
"\n",
|
||||
" vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]\n",
|
||||
" a_init[ir,it,ip] = 1.0 + 2.0*zeta_init[ir,it,ip]\n",
|
||||
" b_init[ir,it,ip] = 1.0 - 2.0*xi_init[ir,it,ip]\n",
|
||||
" c_init[ir,it,ip] = 1.0 + 2.0*xi_init[ir,it,ip]\n",
|
||||
" f_init[ir,it,ip] = -2.0 * eta_init[ir,it,ip]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \\\n",
|
||||
" and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 150.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)\n",
|
||||
" fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip] \n",
|
||||
" a_true[ir,it,ip] = 1.0 + 2.0*zeta_true[ir,it,ip]\n",
|
||||
" b_true[ir,it,ip] = 1.0 - 2.0*xi_true[ir,it,ip]\n",
|
||||
" c_true[ir,it,ip] = 1.0 + 2.0*xi_true[ir,it,ip]\n",
|
||||
" f_true[ir,it,ip] = -2.0 * eta_true[ir,it,ip]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"r_earth = R_earth #6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(r_earth-rr1,r_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init)\n",
|
||||
"fout_init.create_dataset('zeta',data=zeta_init)\n",
|
||||
"fout_init.create_dataset('fun', data=fun_init)\n",
|
||||
"fout_init.create_dataset('fac_a', data=a_init)\n",
|
||||
"fout_init.create_dataset('fac_b', data=b_init)\n",
|
||||
"fout_init.create_dataset('fac_c', data=c_init)\n",
|
||||
"fout_init.create_dataset('fac_f', data=f_init)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true)\n",
|
||||
"fout_true.create_dataset('zeta',data=zeta_true)\n",
|
||||
"fout_true.create_dataset('fun', data=fun_true)\n",
|
||||
"fout_true.create_dataset('fac_a', data=a_true)\n",
|
||||
"fout_true.create_dataset('fac_b', data=b_true)\n",
|
||||
"fout_true.create_dataset('fac_c', data=c_true)\n",
|
||||
"fout_true.create_dataset('fac_f', data=f_true)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(123456789)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 1\n",
|
||||
"n_rec = [1 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"# one source outside of the region\n",
|
||||
"dep_srcs=[]\n",
|
||||
"lon_srcs=[]\n",
|
||||
"lat_srcs=[]\n",
|
||||
"\n",
|
||||
"# teleseismic events\n",
|
||||
"n_src_tele = 10\n",
|
||||
"center_lon = (pp2deg+pp1deg)/2.0\n",
|
||||
"center_lat = (tt2deg+tt1deg)/2.0\n",
|
||||
"r_src = 40 # deg\n",
|
||||
"d_r = 360.0/n_src_tele\n",
|
||||
"\n",
|
||||
"for i in range(n_src_tele):\n",
|
||||
" dep = 50.0\n",
|
||||
" lon = math.cos(d_r*i/180.0*math.pi)*r_src + center_lon\n",
|
||||
" lat = math.sin(d_r*i/180.0*math.pi)*r_src + center_lat\n",
|
||||
" dep_srcs.append(dep)\n",
|
||||
" lon_srcs.append(lon)\n",
|
||||
" lat_srcs.append(lat)\n",
|
||||
"\n",
|
||||
"# regional events\n",
|
||||
"n_src_reg = 0\n",
|
||||
"for i in range(n_src_reg):\n",
|
||||
" dep = random.uniform(r_earth-rr1,r_earth-rr2)\n",
|
||||
" lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
" lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
" dep_srcs.append(dep)\n",
|
||||
" lon_srcs.append(lon)\n",
|
||||
" lat_srcs.append(lat)\n",
|
||||
"\n",
|
||||
"n_src = n_src_tele + n_src_reg\n",
|
||||
"\n",
|
||||
"# create receiver coordinates\n",
|
||||
"n_rec = [20 for i in range(n_src)]\n",
|
||||
"elev_recs=[]\n",
|
||||
"lon_recs=[]\n",
|
||||
"lat_recs=[]\n",
|
||||
"rec_names=[]\n",
|
||||
"for i in range(n_rec[0]):\n",
|
||||
" #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
|
||||
" elev_recs.append(0) # elevation in m\n",
|
||||
" lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
|
||||
" lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
|
||||
" rec_names.append(i)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" dep = dep_srcs[i_src]\n",
|
||||
" lon = lon_srcs[i_src]\n",
|
||||
" lat = lat_srcs[i_src]\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy+\"_\"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
136
test/old_tests/inversion_tele_one_src/1d_ak135.txt
Normal file
136
test/old_tests/inversion_tele_one_src/1d_ak135.txt
Normal file
@@ -0,0 +1,136 @@
|
||||
0.000, 5.8000
|
||||
20.000, 5.8000
|
||||
20.000, 6.5000
|
||||
35.000, 6.5000
|
||||
35.000, 8.0400
|
||||
77.500, 8.0450
|
||||
120.000, 8.0500
|
||||
165.000, 8.1750
|
||||
210.000, 8.3000
|
||||
210.000, 8.3000
|
||||
260.000, 8.4825
|
||||
310.000, 8.6650
|
||||
360.000, 8.8475
|
||||
410.000, 9.0300
|
||||
410.000, 9.3600
|
||||
460.000, 9.5280
|
||||
510.000, 9.6960
|
||||
560.000, 9.8640
|
||||
610.000, 10.0320
|
||||
660.000, 10.2000
|
||||
660.000, 10.7900
|
||||
710.000, 10.9229
|
||||
760.000, 11.0558
|
||||
809.500, 11.1353
|
||||
859.000, 11.2221
|
||||
908.500, 11.3068
|
||||
958.000, 11.3896
|
||||
1007.500, 11.4705
|
||||
1057.000, 11.5495
|
||||
1106.500, 11.6269
|
||||
1156.000, 11.7026
|
||||
1205.500, 11.7766
|
||||
1255.000, 11.8491
|
||||
1304.500, 11.9200
|
||||
1354.000, 11.9895
|
||||
1403.500, 12.0577
|
||||
1453.000, 12.1245
|
||||
1502.500, 12.1912
|
||||
1552.000, 12.2550
|
||||
1601.500, 12.3185
|
||||
1651.000, 12.3819
|
||||
1700.500, 12.4426
|
||||
1750.000, 12.5031
|
||||
1799.500, 12.5631
|
||||
1849.000, 12.6221
|
||||
1898.500, 12.6804
|
||||
1948.000, 12.7382
|
||||
1997.500, 12.7956
|
||||
2047.000, 12.8526
|
||||
2096.500, 12.9096
|
||||
2146.000, 12.9668
|
||||
2195.500, 13.0222
|
||||
2245.000, 13.0783
|
||||
2294.500, 13.1336
|
||||
2344.000, 13.1894
|
||||
2393.500, 13.2465
|
||||
2443.000, 13.3018
|
||||
2492.500, 13.3585
|
||||
2542.000, 13.4156
|
||||
2591.500, 13.4741
|
||||
2640.000, 13.5312
|
||||
2690.000, 13.5900
|
||||
2740.000, 13.6494
|
||||
2740.000, 13.6494
|
||||
2789.670, 13.6530
|
||||
2839.330, 13.6566
|
||||
2891.500, 13.6602
|
||||
2891.500, 8.0000
|
||||
2939.330, 8.0382
|
||||
2989.660, 8.1283
|
||||
3039.990, 8.2213
|
||||
3090.320, 8.3122
|
||||
3140.660, 8.4001
|
||||
3190.990, 8.4861
|
||||
3241.320, 8.5692
|
||||
3291.650, 8.6496
|
||||
3341.980, 8.7283
|
||||
3392.310, 8.8036
|
||||
3442.640, 8.8761
|
||||
3492.970, 8.9461
|
||||
3543.300, 9.0138
|
||||
3593.640, 9.0792
|
||||
3643.970, 9.1426
|
||||
3694.300, 9.2042
|
||||
3744.630, 9.2634
|
||||
3794.960, 9.3205
|
||||
3845.290, 9.3760
|
||||
3895.620, 9.4297
|
||||
3945.950, 9.4814
|
||||
3996.280, 9.5306
|
||||
4046.620, 9.5777
|
||||
4096.950, 9.6232
|
||||
4147.280, 9.6673
|
||||
4197.610, 9.7100
|
||||
4247.940, 9.7513
|
||||
4298.270, 9.7914
|
||||
4348.600, 9.8304
|
||||
4398.930, 9.8682
|
||||
4449.260, 9.9051
|
||||
4499.600, 9.9410
|
||||
4549.930, 9.9761
|
||||
4600.260, 10.0103
|
||||
4650.590, 10.0439
|
||||
4700.920, 10.0768
|
||||
4801.580, 10.1415
|
||||
4851.910, 10.1739
|
||||
4902.240, 10.2049
|
||||
4952.580, 10.2329
|
||||
5002.910, 10.2565
|
||||
5053.240, 10.2745
|
||||
5103.570, 10.2854
|
||||
5153.500, 10.2890
|
||||
5153.500, 11.0427
|
||||
5204.610, 11.0585
|
||||
5255.320, 11.0718
|
||||
5306.040, 11.0850
|
||||
5356.750, 11.0983
|
||||
5407.460, 11.1166
|
||||
5458.170, 11.1316
|
||||
5508.890, 11.1457
|
||||
5559.600, 11.1590
|
||||
5610.310, 11.1715
|
||||
5661.020, 11.1832
|
||||
5711.740, 11.1941
|
||||
5813.160, 11.2134
|
||||
5863.870, 11.2219
|
||||
5914.590, 11.2295
|
||||
5965.300, 11.2364
|
||||
6016.010, 11.2424
|
||||
6066.720, 11.2477
|
||||
6117.440, 11.2521
|
||||
6168.150, 11.2557
|
||||
6218.860, 11.2586
|
||||
6269.570, 11.2606
|
||||
6320.290, 11.2618
|
||||
6371.000, 11.2622
|
||||
789
test/old_tests/inversion_tele_one_src/1d_model.txt
Normal file
789
test/old_tests/inversion_tele_one_src/1d_model.txt
Normal file
@@ -0,0 +1,789 @@
|
||||
5463, 11.3081
|
||||
5465, 11.3046
|
||||
5467, 11.3012
|
||||
5469, 11.2978
|
||||
5471, 11.2944
|
||||
5473, 11.291
|
||||
5475, 11.2876
|
||||
5477, 11.2842
|
||||
5479, 11.2807
|
||||
5481, 11.2773
|
||||
5483, 11.2739
|
||||
5485, 11.2705
|
||||
5487, 11.2671
|
||||
5489, 11.2637
|
||||
5491, 11.2603
|
||||
5493, 11.2568
|
||||
5495, 11.2534
|
||||
5497, 11.25
|
||||
5499, 11.2466
|
||||
5501, 11.2431
|
||||
5503, 11.2395
|
||||
5505, 11.2359
|
||||
5507, 11.2323
|
||||
5509, 11.2288
|
||||
5511, 11.2252
|
||||
5513, 11.2216
|
||||
5515, 11.218
|
||||
5517, 11.2144
|
||||
5519, 11.2108
|
||||
5521, 11.2072
|
||||
5523, 11.2037
|
||||
5525, 11.2001
|
||||
5527, 11.1965
|
||||
5529, 11.1929
|
||||
5531, 11.1893
|
||||
5533, 11.1857
|
||||
5535, 11.1821
|
||||
5537, 11.1785
|
||||
5539, 11.175
|
||||
5541, 11.1714
|
||||
5543, 11.1678
|
||||
5545, 11.1642
|
||||
5547, 11.1606
|
||||
5549, 11.157
|
||||
5551, 11.1534
|
||||
5553, 11.1499
|
||||
5555, 11.1463
|
||||
5557, 11.1427
|
||||
5559, 11.1391
|
||||
5561, 11.1355
|
||||
5563, 11.1319
|
||||
5565, 11.1283
|
||||
5567, 11.1247
|
||||
5569, 11.1212
|
||||
5571, 11.1176
|
||||
5573, 11.114
|
||||
5575, 11.1104
|
||||
5577, 11.1068
|
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||||
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||||
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|
||||
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||||
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||||
6631, 5.8
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||||
6633, 5.8
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||||
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||||
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||||
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6645, 5.8
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2
test/old_tests/inversion_tele_one_src/EARTHQUAKES_tele
Normal file
2
test/old_tests/inversion_tele_one_src/EARTHQUAKES_tele
Normal file
@@ -0,0 +1,2 @@
|
||||
1
|
||||
50.0 40.0 67.5
|
||||
19
test/old_tests/inversion_tele_one_src/README.md
Normal file
19
test/old_tests/inversion_tele_one_src/README.md
Normal file
@@ -0,0 +1,19 @@
|
||||
# Inversion test
|
||||
|
||||
This is a test setup for inversion calculation.
|
||||
|
||||
1. Run all cells of `make_test_model.ipynb` for creating
|
||||
- source, receiver file
|
||||
- true model
|
||||
- initial model
|
||||
|
||||
2. then run TOMOATT forward with `input_params_pre.yml` for calculating the true arrival times at the stations
|
||||
-> this will output src_rec_result.dat file which includes the arrival time at each station
|
||||
|
||||
3. run TOMOATT in inversion mode with `input_params.yml`.
|
||||
|
||||
4. at first, TOMOATT calculates 2d traveltime field for each teleseismic event.
|
||||
TOMOATT will find the event source is teleseismic if the event origin is outside of the simulation domain.
|
||||
Calculated 2d traveltime field is saved in OUTPUT_FILES directory with 2d_travel_time_field_{src_id}.h5
|
||||
2D solver run will be skipped if this file is found by TOMOATT.
|
||||
|
||||
51
test/old_tests/inversion_tele_one_src/STATIONS
Normal file
51
test/old_tests/inversion_tele_one_src/STATIONS
Normal file
@@ -0,0 +1,51 @@
|
||||
50
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||||
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||||
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||||
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||||
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||||
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File diff suppressed because one or more lines are too long
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||||
0
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||||
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||||
1
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
File diff suppressed because one or more lines are too long
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|
||||
88
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
80.00 8.07688 4.46953 3.37471 195.0 80.0
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
355.00 8.81867 4.73840 3.51639 370.0 143.0
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||||
400.00 8.90522 4.76989 3.54325 372.0 143.0
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||||
400.00 9.13397 4.93259 3.72378 366.0 143.0
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||||
450.00 9.38990 5.07842 3.78678 365.0 143.0
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||||
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||||
550.00 9.90185 5.37014 3.91282 363.0 143.0
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||||
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||||
635.00 10.21203 5.54311 3.98399 362.0 143.0
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||||
670.00 10.26622 5.57020 3.99214 362.0 143.0
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||||
670.00 10.75131 5.94508 4.38071 759.0 312.0
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||||
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||||
771.00 11.06557 6.24046 4.44317 730.0 312.0
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||||
871.00 11.24490 6.31091 4.50372 737.0 312.0
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||||
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||||
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||||
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||||
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||||
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||||
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||||
1671.00 12.42075 6.77606 4.95073 779.0 312.0
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||||
1771.00 12.54466 6.82512 5.00299 784.0 312.0
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||||
1871.00 12.66550 6.87289 5.05469 788.0 312.0
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||||
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||||
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||||
2171.00 13.01579 7.01053 5.20713 799.0 312.0
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||||
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||||
2371.00 13.24532 7.09974 5.30724 807.0 312.0
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||||
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||||
2571.00 13.47742 7.18892 5.40681 815.0 312.0
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||||
2671.00 13.59597 7.23403 5.45657 819.0 312.0
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||||
2741.00 13.68041 7.26597 5.49145 822.0 312.0
|
||||
2771.00 13.68753 7.26575 5.50642 823.0 312.0
|
||||
2871.00 13.71168 7.26486 5.55641 826.0 312.0
|
||||
2891.00 13.71660 7.26466 5.56645 826.0 312.0
|
||||
2891.00 8.06482 0.00000 9.90349 57822.0 0.0
|
||||
2971.00 8.19939 0.00000 10.02940 57822.0 0.0
|
||||
3071.00 8.36019 0.00000 10.18134 57822.0 0.0
|
||||
3171.00 8.51298 0.00000 10.32726 57822.0 0.0
|
||||
3271.00 8.65805 0.00000 10.46727 57822.0 0.0
|
||||
3371.00 8.79573 0.00000 10.60152 57822.0 0.0
|
||||
3471.00 8.92632 0.00000 10.73012 57822.0 0.0
|
||||
3571.00 9.05015 0.00000 10.85321 57822.0 0.0
|
||||
3671.00 9.16752 0.00000 10.97091 57822.0 0.0
|
||||
3771.00 9.27867 0.00000 11.08335 57822.0 0.0
|
||||
3871.00 9.38418 0.00000 11.19067 57822.0 0.0
|
||||
3971.00 9.48409 0.00000 11.29298 57822.0 0.0
|
||||
4071.00 9.57881 0.00000 11.39042 57822.0 0.0
|
||||
4171.00 9.66865 0.00000 11.48311 57822.0 0.0
|
||||
4271.00 9.75393 0.00000 11.57119 57822.0 0.0
|
||||
4371.00 9.83496 0.00000 11.65478 57822.0 0.0
|
||||
4471.00 9.91206 0.00000 11.73401 57822.0 0.0
|
||||
4571.00 9.98554 0.00000 11.80900 57822.0 0.0
|
||||
4671.00 10.05572 0.00000 11.87990 57822.0 0.0
|
||||
4771.00 10.12291 0.00000 11.94682 57822.0 0.0
|
||||
4871.00 10.18743 0.00000 12.00989 57822.0 0.0
|
||||
4971.00 10.24959 0.00000 12.06924 57822.0 0.0
|
||||
5071.00 10.30971 0.00000 12.12500 57822.0 0.0
|
||||
5149.50 10.35568 0.00000 12.16634 57822.0 0.0
|
||||
5149.50 11.02827 3.50432 12.76360 445.0 85.0
|
||||
5171.00 11.03643 3.51002 12.77493 445.0 85.0
|
||||
5271.00 11.07249 3.53522 12.82501 443.0 85.0
|
||||
5371.00 11.10542 3.55823 12.87073 440.0 85.0
|
||||
5471.00 11.13521 3.57905 12.91211 439.0 85.0
|
||||
5571.00 11.16186 3.59767 12.94912 437.0 85.0
|
||||
5671.00 11.18538 3.61411 12.98178 436.0 85.0
|
||||
5771.00 11.20576 3.62835 13.01009 434.0 85.0
|
||||
5871.00 11.22301 3.64041 13.03404 433.0 85.0
|
||||
5971.00 11.23712 3.65027 13.05364 432.0 85.0
|
||||
6071.00 11.24809 3.65794 13.06888 432.0 85.0
|
||||
6171.00 11.25593 3.66342 13.07977 431.0 85.0
|
||||
6271.00 11.26064 3.66670 13.08630 431.0 85.0
|
||||
6371.00 11.26220 3.66780 13.08848 431.0 85.0
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
47
test/old_tests/inversion_tele_one_src/input_params.yml
Normal file
47
test/old_tests/inversion_tele_one_src/input_params.yml
Normal file
@@ -0,0 +1,47 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'OUTPUT_FILES/src_rec_file_forward.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_init.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 1 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 5 # number of inversion grid sets
|
||||
n_inv_dep_lat_lon : [11,10,10] # number of the base inversion grid points
|
||||
min_max_dep_inv : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat_inv : [30.0,50.0] # latitude in degree
|
||||
min_max_lon_inv : [15.0,40.0] # longitude in degree
|
||||
|
||||
#smooth_method : 1 # 0: multigrid parametrization, 1: laplacian smoothing with CG
|
||||
#l_smooth_rtp : [0.9,0.9,0.9] # smoothing coefficients for each direction
|
||||
|
||||
max_iterations_inv : 100 # maximum number of inversion iterations
|
||||
step_size : 0.01 # step size for inversion
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
use_gpu : 0
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 100
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
output_file_format : 0 # 0: hdf5, 1: ascii
|
||||
|
||||
34
test/old_tests/inversion_tele_one_src/input_params_pre.yml
Normal file
34
test/old_tests/inversion_tele_one_src/input_params_pre.yml
Normal file
@@ -0,0 +1,34 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [55,55,55] # number of nodes
|
||||
|
||||
source :
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [1,2,2] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-5
|
||||
max_iterations : 1000
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
output_file_format : 0 # 0: hdf5, 1: ascii
|
||||
|
||||
|
||||
412
test/old_tests/inversion_tele_one_src/make_test_model.ipynb
Normal file
412
test/old_tests/inversion_tele_one_src/make_test_model.ipynb
Normal file
@@ -0,0 +1,412 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# notebook for create init and true test model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"\n",
|
||||
"# grid\n",
|
||||
"R_earth = 6371.0 #6378.1370\n",
|
||||
"\n",
|
||||
"rr1=6070\n",
|
||||
"rr2=6400\n",
|
||||
"tt1=(30.0-1.5)/180*math.pi\n",
|
||||
"tt2=(50.0+1.5)/180*math.pi\n",
|
||||
"pp1=(15.0-1.5)/180*math.pi\n",
|
||||
"pp2=(40.0+1.5)/180*math.pi\n",
|
||||
"\n",
|
||||
"n_rtp = [55,55,55]\n",
|
||||
"dr = (rr2-rr1)/(n_rtp[0]-1)\n",
|
||||
"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
|
||||
"dp = (pp2-pp1)/(n_rtp[2]-1)\n",
|
||||
"rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])\n",
|
||||
"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
|
||||
"pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])\n",
|
||||
"\n",
|
||||
"# initial model\n",
|
||||
"gamma = 0.0\n",
|
||||
"#s0 = 1.0/6.0\n",
|
||||
"slow_p=0.04\n",
|
||||
"ani_p=0.03\n",
|
||||
"\n",
|
||||
"eta_init = np.zeros(n_rtp)\n",
|
||||
"xi_init = np.zeros(n_rtp)\n",
|
||||
"zeta_init = np.zeros(n_rtp)\n",
|
||||
"fun_init = np.zeros(n_rtp)\n",
|
||||
"vel_init = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"# true model\n",
|
||||
"eta_true = np.zeros(n_rtp)\n",
|
||||
"xi_true = np.zeros(n_rtp)\n",
|
||||
"zeta_true = np.zeros(n_rtp)\n",
|
||||
"fun_true = np.zeros(n_rtp)\n",
|
||||
"vel_true = np.zeros(n_rtp)\n",
|
||||
"\n",
|
||||
"c=0\n",
|
||||
"for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" #eta_init[ir,it,ip] = 0.0\n",
|
||||
" #xi_init[ir,it,ip] = 0.0\n",
|
||||
" zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)\n",
|
||||
" \n",
|
||||
" if (rr[ir]>6351):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)\n",
|
||||
" elif (rr[ir]>6336):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)\n",
|
||||
" elif (rr[ir]>5961):\n",
|
||||
" fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1) \n",
|
||||
" else:\n",
|
||||
" fun_init[ir,it,ip] = 1.0/9.0\n",
|
||||
"\n",
|
||||
" vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]\n",
|
||||
"\n",
|
||||
" # true model\n",
|
||||
" if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \\\n",
|
||||
" and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \\\n",
|
||||
" and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):\n",
|
||||
" c+=1\n",
|
||||
" sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \\\n",
|
||||
" *math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)\n",
|
||||
" else:\n",
|
||||
" sigma = 0.0\n",
|
||||
"\n",
|
||||
" if sigma < 0:\n",
|
||||
" psi = 60.0/180.0*math.pi\n",
|
||||
" elif sigma > 0:\n",
|
||||
" psi = 150.0/180.0*math.pi\n",
|
||||
" else:\n",
|
||||
" psi = 0.0\n",
|
||||
"\n",
|
||||
" eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
|
||||
" xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
|
||||
" zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)\n",
|
||||
" fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)\n",
|
||||
" vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip] \n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"r_earth = R_earth #6378.1370\n",
|
||||
"print(\"depminmax {} {}\".format(r_earth-rr1,r_earth-rr2))\n",
|
||||
"print(c)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out\n",
|
||||
"import h5py\n",
|
||||
"\n",
|
||||
"fout_init = h5py.File('test_model_init.h5', 'w')\n",
|
||||
"fout_true = h5py.File('test_model_true.h5', 'w')\n",
|
||||
"\n",
|
||||
"# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init\n",
|
||||
"fout_init.create_dataset('eta', data=eta_init)\n",
|
||||
"fout_init.create_dataset('xi', data=xi_init)\n",
|
||||
"fout_init.create_dataset('zeta',data=zeta_init)\n",
|
||||
"fout_init.create_dataset('vel', data=vel_init)\n",
|
||||
"\n",
|
||||
"# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true\n",
|
||||
"fout_true.create_dataset('eta', data=eta_true)\n",
|
||||
"fout_true.create_dataset('xi', data=xi_true)\n",
|
||||
"fout_true.create_dataset('zeta',data=zeta_true)\n",
|
||||
"fout_true.create_dataset('vel', data=vel_true)\n",
|
||||
"\n",
|
||||
"fout_init.close()\n",
|
||||
"fout_true.close()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# prepare src station file\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
" 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event\n",
|
||||
" 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec\n",
|
||||
" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
|
||||
" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
|
||||
"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"random.seed(123456789)\n",
|
||||
"\n",
|
||||
"# dummys\n",
|
||||
"year_dummy = 1998\n",
|
||||
"month_dummy = 1\n",
|
||||
"day_dummy = 1\n",
|
||||
"hour_dummy = 0\n",
|
||||
"minute_dummy = 0\n",
|
||||
"second_dummy = 0\n",
|
||||
"mag_dummy = 3.0\n",
|
||||
"id_dummy = 1000\n",
|
||||
"st_name_dummy = 'AAAA'\n",
|
||||
"phase_dummy = 'P'\n",
|
||||
"dist_dummy = 100.0\n",
|
||||
"arriv_t_dummy = 0.0\n",
|
||||
"\n",
|
||||
"tt1deg = tt1 * 180.0/math.pi\n",
|
||||
"tt2deg = tt2 * 180.0/math.pi\n",
|
||||
"pp1deg = pp1 * 180.0/math.pi\n",
|
||||
"pp2deg = pp2 * 180.0/math.pi\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"n_src = 1\n",
|
||||
"n_rec = [1 for x in range(n_src)]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"pos_src=[]\n",
|
||||
"pos_rec=[]\n",
|
||||
"\n",
|
||||
"# teleseismic events\n",
|
||||
"n_src_tele = 1\n",
|
||||
"center_lon = (pp2deg+pp1deg)/2.0\n",
|
||||
"center_lat = (tt2deg+tt1deg)/2.0\n",
|
||||
"r_src = 40 # deg\n",
|
||||
"d_r = 360.0/n_src_tele\n",
|
||||
"\n",
|
||||
"# use fixed coordinate for test\n",
|
||||
"dep_srcs = [50.0]\n",
|
||||
"lon_srcs = [67.5]\n",
|
||||
"lat_srcs = [40.0]\n",
|
||||
"\n",
|
||||
"elev_recs = []\n",
|
||||
"lon_recs = []\n",
|
||||
"lat_recs = []\n",
|
||||
"\n",
|
||||
"# read STATIONS\n",
|
||||
"f = open('fortran_code/ega5/input/STATIONS', 'r')\n",
|
||||
"for line in f:\n",
|
||||
" lines.append(line)\n",
|
||||
"f.close()\n",
|
||||
"\n",
|
||||
"n_rec_tmp=0\n",
|
||||
"for l in lines:\n",
|
||||
" if l[0] == '#':\n",
|
||||
" continue\n",
|
||||
" else:\n",
|
||||
" items = l.split()\n",
|
||||
" if (len(items) == 3):\n",
|
||||
" elev_recs.append(float(items[0]))\n",
|
||||
" lat_recs.append(float(items[1]))\n",
|
||||
" lon_recs.append(float(items[2]))\n",
|
||||
" n_rec_tmp += 1\n",
|
||||
"\n",
|
||||
"n_rec[0] = n_rec_tmp\n",
|
||||
"\n",
|
||||
"#for i in range(n_src_tele):\n",
|
||||
"# dep = 50.0\n",
|
||||
"# lon = math.cos(d_r*i/180.0*math.pi)*r_src + center_lon\n",
|
||||
"# lat = math.sin(d_r*i/180.0*math.pi)*r_src + center_lat\n",
|
||||
"# dep_srcs.append(dep)\n",
|
||||
"# lon_srcs.append(lon)\n",
|
||||
"# lat_srcs.append(lat)\n",
|
||||
"#\n",
|
||||
"## regional events\n",
|
||||
"#n_src_reg = 0\n",
|
||||
"#for i in range(n_src_reg):\n",
|
||||
"# dep = random.uniform(r_earth-rr1,r_earth-rr2)\n",
|
||||
"# lon = random.uniform(pp1deg,pp2deg)\n",
|
||||
"# lat = random.uniform(tt1deg,tt2deg)\n",
|
||||
"# dep_srcs.append(dep)\n",
|
||||
"# lon_srcs.append(lon)\n",
|
||||
"# lat_srcs.append(lat)\n",
|
||||
"#\n",
|
||||
"#n_src = n_src_tele + n_src_reg\n",
|
||||
"#\n",
|
||||
"## create receiver coordinates\n",
|
||||
"#n_rec = [50 for i in range(n_src)]\n",
|
||||
"#elev_recs=[]\n",
|
||||
"#lon_recs=[]\n",
|
||||
"#lat_recs=[]\n",
|
||||
"#rec_names=[]\n",
|
||||
"#for i in range(n_rec[0]):\n",
|
||||
"# #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
|
||||
"# elev_recs.append(0) # elevation in m\n",
|
||||
"# lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
|
||||
"# lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
|
||||
"# rec_names.append(i)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# create dummy src\n",
|
||||
"lines=[]\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" # define one point in the domain (rr1 bottom, rr2 top)\n",
|
||||
" dep = dep_srcs[i_src]\n",
|
||||
" lon = lon_srcs[i_src]\n",
|
||||
" lat = lat_srcs[i_src]\n",
|
||||
"\n",
|
||||
" src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]\n",
|
||||
" lines.append(src)\n",
|
||||
"\n",
|
||||
" pos_src.append([lon,lat,dep])\n",
|
||||
"\n",
|
||||
" # create dummy station\n",
|
||||
" for i_rec in range(n_rec[i_src]):\n",
|
||||
" #elev_rec = random.uniform(0.0,-10.0) # elevation in m\n",
|
||||
" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
|
||||
" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
|
||||
"\n",
|
||||
" rec = [i_src, i_rec, st_name_dummy+\"_\"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, dist_dummy, arriv_t_dummy]\n",
|
||||
" lines.append(rec)\n",
|
||||
"\n",
|
||||
" pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])\n",
|
||||
"\n",
|
||||
"# write out ev_arrivals file\n",
|
||||
"fname = 'src_rec_test.dat'\n",
|
||||
"\n",
|
||||
"with open(fname, 'w') as f:\n",
|
||||
" for line in lines:\n",
|
||||
" for elem in line:\n",
|
||||
" f.write('{} '.format(elem))\n",
|
||||
" f.write('\\n')\n",
|
||||
" "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# draw src and rec positions\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"for i_src in range(n_src):\n",
|
||||
" plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot receivers\n",
|
||||
"for i_rec in range(n_rec[0]):\n",
|
||||
" plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# output source and receiver file for fortran code\n",
|
||||
"fname_source = \"EARTHQUAKES_tele\"\n",
|
||||
"fname_station=\"STATIONS\"\n",
|
||||
"\n",
|
||||
"# write out number of sources\n",
|
||||
"with open(fname_source, 'w') as f:\n",
|
||||
" f.write('{}\\n'.format(n_src))\n",
|
||||
" # write out depth lat lon \n",
|
||||
" for i_src in range(n_src):\n",
|
||||
" f.write('{} {} {}\\n'.format(dep_srcs[i_src],lat_srcs[i_src],lon_srcs[i_src]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write out number of stations\n",
|
||||
"with open(fname_station, 'w') as f:\n",
|
||||
" f.write('{}\\n'.format(n_rec[0]))\n",
|
||||
" # write out depth lat lon (convert elevation to depth)\n",
|
||||
" for i_rec in range(n_rec[0]):\n",
|
||||
" f.write('{} {} {}\\n'.format(elev_recs[i_rec],lat_recs[i_rec],lon_recs[i_rec]))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# write out in ASCIII\n",
|
||||
"\n",
|
||||
"#\n",
|
||||
"\n",
|
||||
"fname_init = 'test_model_init.dat'\n",
|
||||
"fname_true = 'test_model_true.dat'\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write init model\n",
|
||||
"with open(fname_init, 'w') as f:\n",
|
||||
" # write nodes in rtp\n",
|
||||
" for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
|
||||
" f.write(\"{:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f}\\n\".format(eta_init[ir,it,ip],xi_init[ir,it,ip],zeta_init[ir,it,ip],fun_init[ir,it,ip],vel_init[ir,it,ip],a_init[ir,it,ip],b_init[ir,it,ip],c_init[ir,it,ip],f_init[ir,it,ip]))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# write true model\n",
|
||||
"with open(fname_true, 'w') as f:\n",
|
||||
" # write nodes in rtp\n",
|
||||
" for ir in range(n_rtp[2]):\n",
|
||||
" for it in range(n_rtp[1]):\n",
|
||||
" for ip in range(n_rtp[0]):\n",
|
||||
" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
|
||||
" f.write(\"{:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f}\\n\".format(eta_true[ir,it,ip],xi_true[ir,it,ip],zeta_true[ir,it,ip],fun_true[ir,it,ip],vel_true[ir,it,ip],a_true[ir,it,ip],b_true[ir,it,ip],c_true[ir,it,ip],f_true[ir,it,ip]))\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "fbd0b2a7df497f398d93ab2f589d8a5daa3108cfb7ff2b90736653cca3aeadc0"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
331
test/old_tests/inversion_tele_one_src/make_test_model.py
Normal file
331
test/old_tests/inversion_tele_one_src/make_test_model.py
Normal file
@@ -0,0 +1,331 @@
|
||||
# %% [markdown]
|
||||
# # notebook for create init and true test model
|
||||
|
||||
# %%
|
||||
import numpy as np
|
||||
import math
|
||||
|
||||
# grid
|
||||
R_earth = 6371.0 #6378.1370
|
||||
|
||||
rr1=6070
|
||||
rr2=6400
|
||||
tt1=(30.0-1.5)/180*math.pi
|
||||
tt2=(50.0+1.5)/180*math.pi
|
||||
pp1=(15.0-1.5)/180*math.pi
|
||||
pp2=(40.0+1.5)/180*math.pi
|
||||
|
||||
n_rtp = [55,55,55]
|
||||
dr = (rr2-rr1)/(n_rtp[0]-1)
|
||||
dt = (tt2-tt1)/(n_rtp[1]-1)
|
||||
dp = (pp2-pp1)/(n_rtp[2]-1)
|
||||
rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])
|
||||
tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
|
||||
pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])
|
||||
|
||||
# initial model
|
||||
gamma = 0.0
|
||||
#s0 = 1.0/6.0
|
||||
slow_p=0.04
|
||||
ani_p=0.03
|
||||
|
||||
eta_init = np.zeros(n_rtp)
|
||||
xi_init = np.zeros(n_rtp)
|
||||
zeta_init = np.zeros(n_rtp)
|
||||
fun_init = np.zeros(n_rtp)
|
||||
vel_init = np.zeros(n_rtp)
|
||||
|
||||
# true model
|
||||
eta_true = np.zeros(n_rtp)
|
||||
xi_true = np.zeros(n_rtp)
|
||||
zeta_true = np.zeros(n_rtp)
|
||||
fun_true = np.zeros(n_rtp)
|
||||
vel_true = np.zeros(n_rtp)
|
||||
|
||||
c=0
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
#eta_init[ir,it,ip] = 0.0
|
||||
#xi_init[ir,it,ip] = 0.0
|
||||
zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)
|
||||
|
||||
if (rr[ir]>6351):
|
||||
fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)
|
||||
elif (rr[ir]>6336):
|
||||
fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)
|
||||
elif (rr[ir]>5961):
|
||||
fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1)
|
||||
else:
|
||||
fun_init[ir,it,ip] = 1.0/9.0
|
||||
|
||||
vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]
|
||||
|
||||
# true model
|
||||
if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \
|
||||
and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \
|
||||
and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):
|
||||
c+=1
|
||||
sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \
|
||||
*math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \
|
||||
*math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)
|
||||
else:
|
||||
sigma = 0.0
|
||||
|
||||
if sigma < 0:
|
||||
psi = 60.0/180.0*math.pi
|
||||
elif sigma > 0:
|
||||
psi = 150.0/180.0*math.pi
|
||||
else:
|
||||
psi = 0.0
|
||||
|
||||
eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)
|
||||
xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)
|
||||
zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)
|
||||
fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)
|
||||
vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip]
|
||||
|
||||
|
||||
|
||||
r_earth = R_earth #6378.1370
|
||||
print("depminmax {} {}".format(r_earth-rr1,r_earth-rr2))
|
||||
print(c)
|
||||
|
||||
|
||||
# %%
|
||||
# write out
|
||||
import h5py
|
||||
|
||||
fout_init = h5py.File('test_model_init.h5', 'w')
|
||||
fout_true = h5py.File('test_model_true.h5', 'w')
|
||||
|
||||
# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
|
||||
fout_init.create_dataset('eta', data=eta_init)
|
||||
fout_init.create_dataset('xi', data=xi_init)
|
||||
fout_init.create_dataset('zeta',data=zeta_init)
|
||||
fout_init.create_dataset('vel', data=vel_init)
|
||||
|
||||
# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
|
||||
fout_true.create_dataset('eta', data=eta_true)
|
||||
fout_true.create_dataset('xi', data=xi_true)
|
||||
fout_true.create_dataset('zeta',data=zeta_true)
|
||||
fout_true.create_dataset('vel', data=vel_true)
|
||||
|
||||
fout_init.close()
|
||||
fout_true.close()
|
||||
|
||||
|
||||
# %% [markdown]
|
||||
# # prepare src station file
|
||||
#
|
||||
# ```
|
||||
# 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event
|
||||
# 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec
|
||||
# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
|
||||
# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
|
||||
#
|
||||
# ```
|
||||
|
||||
# %%
|
||||
import random
|
||||
random.seed(123456789)
|
||||
|
||||
# dummys
|
||||
year_dummy = 1998
|
||||
month_dummy = 1
|
||||
day_dummy = 1
|
||||
hour_dummy = 0
|
||||
minute_dummy = 0
|
||||
second_dummy = 0
|
||||
mag_dummy = 3.0
|
||||
id_dummy = 1000
|
||||
st_name_dummy = 'AAAA'
|
||||
phase_dummy = 'P'
|
||||
arriv_t_dummy = 0.0
|
||||
|
||||
tt1deg = tt1 * 180.0/math.pi
|
||||
tt2deg = tt2 * 180.0/math.pi
|
||||
pp1deg = pp1 * 180.0/math.pi
|
||||
pp2deg = pp2 * 180.0/math.pi
|
||||
|
||||
|
||||
n_src = 1
|
||||
n_rec = [1 for x in range(n_src)]
|
||||
|
||||
|
||||
lines = []
|
||||
|
||||
pos_src=[]
|
||||
pos_rec=[]
|
||||
|
||||
# teleseismic events
|
||||
n_src_tele = 1
|
||||
center_lon = (pp2deg+pp1deg)/2.0
|
||||
center_lat = (tt2deg+tt1deg)/2.0
|
||||
r_src = 40 # deg
|
||||
d_r = 360.0/n_src_tele
|
||||
|
||||
# use fixed coordinate for test
|
||||
dep_srcs = [50.0]
|
||||
lon_srcs = [67.5]
|
||||
lat_srcs = [40.0]
|
||||
|
||||
elev_recs = []
|
||||
lon_recs = []
|
||||
lat_recs = []
|
||||
|
||||
# read STATIONS
|
||||
f = open('fortran_code/ega5/input/STATIONS', 'r')
|
||||
for line in f:
|
||||
lines.append(line)
|
||||
f.close()
|
||||
|
||||
n_rec_tmp=0
|
||||
for l in lines:
|
||||
if l[0] == '#':
|
||||
continue
|
||||
else:
|
||||
items = l.split()
|
||||
if (len(items) == 3):
|
||||
elev_recs.append(float(items[0]))
|
||||
lat_recs.append(float(items[1]))
|
||||
lon_recs.append(float(items[2]))
|
||||
n_rec_tmp += 1
|
||||
|
||||
n_rec[0] = n_rec_tmp
|
||||
|
||||
#for i in range(n_src_tele):
|
||||
# dep = 50.0
|
||||
# lon = math.cos(d_r*i/180.0*math.pi)*r_src + center_lon
|
||||
# lat = math.sin(d_r*i/180.0*math.pi)*r_src + center_lat
|
||||
# dep_srcs.append(dep)
|
||||
# lon_srcs.append(lon)
|
||||
# lat_srcs.append(lat)
|
||||
#
|
||||
## regional events
|
||||
#n_src_reg = 0
|
||||
#for i in range(n_src_reg):
|
||||
# dep = random.uniform(r_earth-rr1,r_earth-rr2)
|
||||
# lon = random.uniform(pp1deg,pp2deg)
|
||||
# lat = random.uniform(tt1deg,tt2deg)
|
||||
# dep_srcs.append(dep)
|
||||
# lon_srcs.append(lon)
|
||||
# lat_srcs.append(lat)
|
||||
#
|
||||
#n_src = n_src_tele + n_src_reg
|
||||
#
|
||||
## create receiver coordinates
|
||||
#n_rec = [50 for i in range(n_src)]
|
||||
#elev_recs=[]
|
||||
#lon_recs=[]
|
||||
#lat_recs=[]
|
||||
#rec_names=[]
|
||||
#for i in range(n_rec[0]):
|
||||
# #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m
|
||||
# elev_recs.append(0) # elevation in m
|
||||
# lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))
|
||||
# lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))
|
||||
# rec_names.append(i)
|
||||
|
||||
|
||||
|
||||
# create dummy src
|
||||
lines=[]
|
||||
for i_src in range(n_src):
|
||||
# define one point in the domain (rr1 bottom, rr2 top)
|
||||
dep = dep_srcs[i_src]
|
||||
lon = lon_srcs[i_src]
|
||||
lat = lat_srcs[i_src]
|
||||
|
||||
src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]
|
||||
lines.append(src)
|
||||
|
||||
pos_src.append([lon,lat,dep])
|
||||
|
||||
# create dummy station
|
||||
for i_rec in range(n_rec[i_src]):
|
||||
#elev_rec = random.uniform(0.0,-10.0) # elevation in m
|
||||
#lon_rec = random.uniform(pp1deg,pp2deg)
|
||||
#lat_rec = random.uniform(tt1deg,tt2deg)
|
||||
|
||||
rec = [i_src, i_rec, st_name_dummy+"_"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, arriv_t_dummy]
|
||||
lines.append(rec)
|
||||
|
||||
pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])
|
||||
|
||||
# write out ev_arrivals file
|
||||
fname = 'src_rec_test.dat'
|
||||
|
||||
with open(fname, 'w') as f:
|
||||
for line in lines:
|
||||
for elem in line:
|
||||
f.write('{} '.format(elem))
|
||||
f.write('\n')
|
||||
|
||||
|
||||
# %%
|
||||
# draw src and rec positions
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
for i_src in range(n_src):
|
||||
plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
|
||||
|
||||
# %%
|
||||
# plot receivers
|
||||
for i_rec in range(n_rec[0]):
|
||||
plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
|
||||
|
||||
# %%
|
||||
# output source and receiver file for fortran code
|
||||
fname_source = "EARTHQUAKES_tele"
|
||||
fname_station="STATIONS"
|
||||
|
||||
# write out number of sources
|
||||
with open(fname_source, 'w') as f:
|
||||
f.write('{}\n'.format(n_src))
|
||||
# write out depth lat lon
|
||||
for i_src in range(n_src):
|
||||
f.write('{} {} {}\n'.format(dep_srcs[i_src],lat_srcs[i_src],lon_srcs[i_src]))
|
||||
|
||||
|
||||
# write out number of stations
|
||||
with open(fname_station, 'w') as f:
|
||||
f.write('{}\n'.format(n_rec[0]))
|
||||
# write out depth lat lon (convert elevation to depth)
|
||||
for i_rec in range(n_rec[0]):
|
||||
f.write('{} {} {}\n'.format(elev_recs[i_rec],lat_recs[i_rec],lon_recs[i_rec]))
|
||||
|
||||
# %%
|
||||
# write out in ASCIII
|
||||
|
||||
#
|
||||
|
||||
fname_init = 'test_model_init.dat'
|
||||
fname_true = 'test_model_true.dat'
|
||||
|
||||
|
||||
# write init model
|
||||
with open(fname_init, 'w') as f:
|
||||
# write nodes in rtp
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
# write out eta xi zeta fun fac_a fac_b fac_c fac_f
|
||||
f.write("{:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f}\n".format(eta_init[ir,it,ip],xi_init[ir,it,ip],zeta_init[ir,it,ip],fun_init[ir,it,ip],vel_init[ir,it,ip],a_init[ir,it,ip],b_init[ir,it,ip],c_init[ir,it,ip],f_init[ir,it,ip]))
|
||||
|
||||
|
||||
# write true model
|
||||
with open(fname_true, 'w') as f:
|
||||
# write nodes in rtp
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
# write out eta xi zeta fun fac_a fac_b fac_c fac_f
|
||||
f.write("{:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f} {:.16f}\n".format(eta_true[ir,it,ip],xi_true[ir,it,ip],zeta_true[ir,it,ip],fun_true[ir,it,ip],vel_true[ir,it,ip],a_true[ir,it,ip],b_true[ir,it,ip],c_true[ir,it,ip],f_true[ir,it,ip]))
|
||||
|
||||
|
||||
|
||||
# %%
|
||||
|
||||
|
||||
|
||||
52
test/old_tests/only_source/README.md
Normal file
52
test/old_tests/only_source/README.md
Normal file
@@ -0,0 +1,52 @@
|
||||
# Example for Solver only mode
|
||||
|
||||
This example shows how to use the Solver only mode of the tool.
|
||||
|
||||
## compile TOMOATT with solver_only executable
|
||||
|
||||
Uncomment "src/TOMOATT_solver_only.cxx" and "src/TOMOATT_2d_precalc.cxx" in CMakeLists.txt to compile the solver_only executable as below.
|
||||
|
||||
```cmake
|
||||
# add one by one
|
||||
set(APP_SOURCES
|
||||
src/TOMOATT.cxx
|
||||
src/TOMOATT_solver_only.cxx
|
||||
src/TOMOATT_2d_precalc.cxx
|
||||
#src/SrcRecWeight.cxx
|
||||
)
|
||||
```
|
||||
|
||||
Then recompile the code in the build directory.
|
||||
|
||||
|
||||
## pre calculation of source boudary conditions
|
||||
|
||||
As the 2d solver is not parallelized for one single teleseismic source yet, what user can do is calculate multiple teleseismic sources at the same time using simultaneous run.
|
||||
The precalculation of source boundary conditions can be done by running the following command:
|
||||
|
||||
```bash
|
||||
mpirun -n 8 ../../build/bin/TOMOATT_2d_precalc -i input_params_pre.yml
|
||||
```
|
||||
|
||||
## run the solver_only executable
|
||||
|
||||
Before running the solver_only executable, you need to prepare the input files by running:
|
||||
|
||||
```python
|
||||
python make_test_model.py
|
||||
```
|
||||
|
||||
This creates a src_only_test.dat which includes 8 sources without any receiver.
|
||||
|
||||
Then run the solver_only executable as below.
|
||||
|
||||
```bash
|
||||
mpirun -n 8 ../../build/bin/TOMOATT_solver_only -i src_only_test.dat
|
||||
```
|
||||
|
||||
## check the output files
|
||||
The result file can be visualize with paraview:
|
||||
```bash
|
||||
paraview OUTPUT_FILES/out_data_sim.xmf
|
||||
```
|
||||
or directly open with python etc. Please refer the check_3d_out.ipynb for more details.
|
||||
91
test/old_tests/only_source/check_3d_out.ipynb
Normal file
91
test/old_tests/only_source/check_3d_out.ipynb
Normal file
File diff suppressed because one or more lines are too long
33
test/old_tests/only_source/input_params.yml
Normal file
33
test/old_tests/only_source/input_params.yml
Normal file
@@ -0,0 +1,33 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
src_rec_file : 'src_only_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver # SHOLD BE 0 FOR SOURCE ONLY RUN
|
||||
|
||||
model :
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [2,1,1] # number of subdomains
|
||||
nproc_sub : 2 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 500
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
is_output_source_field : 1 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
|
||||
is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
|
||||
is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
|
||||
33
test/old_tests/only_source/input_params_pre.yml
Normal file
33
test/old_tests/only_source/input_params_pre.yml
Normal file
@@ -0,0 +1,33 @@
|
||||
version : 2
|
||||
|
||||
domain :
|
||||
min_max_dep : [-10.0, 10.0] # depth in km
|
||||
min_max_lat : [37.7,42.3] # latitude in degree
|
||||
min_max_lon : [22.7,27.3] # longitude in degree
|
||||
n_rtp : [10,50,50] # number of nodes
|
||||
|
||||
source :
|
||||
src_rec_file : 'src_only_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 0 # swap source and receiver # SHOLD BE 0 FOR SOURCE ONLY RUN
|
||||
|
||||
model :
|
||||
init_model_path : './test_model_true.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
|
||||
parallel : # no mean for 2d pre calculation
|
||||
n_sims : 8 # number of simultaneous run. use as much as possible for 2d source preparation
|
||||
ndiv_rtp : [1,1,1] # number of subdomains
|
||||
nproc_sub : 1 # number of subprocess used for each subdomain
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 500
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
is_output_source_field : 1 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
|
||||
is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
|
||||
is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
|
||||
200
test/old_tests/only_source/make_test_model.py
Normal file
200
test/old_tests/only_source/make_test_model.py
Normal file
@@ -0,0 +1,200 @@
|
||||
# %% [markdown]
|
||||
# # notebook for create init and true test model
|
||||
|
||||
# %%
|
||||
import numpy as np
|
||||
import math
|
||||
|
||||
# grid
|
||||
R_earth = 6371.0
|
||||
|
||||
rr1=6361
|
||||
rr2=6381
|
||||
tt1=(38.0-0.3)/180*math.pi
|
||||
tt2=(42.0+0.3)/180*math.pi
|
||||
pp1=(23.0-0.3)/180*math.pi
|
||||
pp2=(27.0+0.3)/180*math.pi
|
||||
|
||||
n_rtp = [10,50,50]
|
||||
dr = (rr2-rr1)/(n_rtp[0]-1)
|
||||
dt = (tt2-tt1)/(n_rtp[1]-1)
|
||||
dp = (pp2-pp1)/(n_rtp[2]-1)
|
||||
rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])
|
||||
tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
|
||||
pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])
|
||||
|
||||
# initial model
|
||||
gamma = 0.0
|
||||
s0 = 1.0/6.0
|
||||
slow_p=0.06
|
||||
ani_p=0.04
|
||||
|
||||
eta_init = np.zeros(n_rtp)
|
||||
xi_init = np.zeros(n_rtp)
|
||||
zeta_init = np.zeros(n_rtp)
|
||||
fun_init = np.zeros(n_rtp)
|
||||
vel_init = np.zeros(n_rtp)
|
||||
|
||||
# true model
|
||||
eta_true = np.zeros(n_rtp)
|
||||
xi_true = np.zeros(n_rtp)
|
||||
zeta_true = np.zeros(n_rtp)
|
||||
fun_true = np.zeros(n_rtp)
|
||||
vel_true = np.zeros(n_rtp)
|
||||
|
||||
c=0
|
||||
for ir in range(n_rtp[0]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[2]):
|
||||
# already initialized above
|
||||
#eta_init[ir,it,ip] = 0.0
|
||||
#xi_init[ir,it,ip] = 0.0
|
||||
zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)
|
||||
fun_init[ir,it,ip] = s0
|
||||
vel_init[ir,it,ip] = 1.0/s0
|
||||
|
||||
# true model
|
||||
if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \
|
||||
and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):
|
||||
c+=1
|
||||
sigma = math.sin(2.0*math.pi*(tt[it]-38.0/180.0*math.pi)/(4.0/180.0*math.pi))*math.sin(2.0*math.pi*(pp[ip]-23.0/180.0*math.pi)/(4.0/180.0*math.pi))
|
||||
else:
|
||||
sigma = 0.0
|
||||
|
||||
if sigma < 0:
|
||||
psi = 60.0/180.0*math.pi
|
||||
elif sigma > 0:
|
||||
psi = 120.0/180.0*math.pi
|
||||
else:
|
||||
psi = 0.0
|
||||
|
||||
eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)
|
||||
xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)
|
||||
zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)
|
||||
fun_true[ir,it,ip] = s0/(1.0+sigma*slow_p)
|
||||
vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip]
|
||||
|
||||
|
||||
#r_earth = 6378.1370
|
||||
print("depminmax {} {}".format(R_earth-rr1,R_earth-rr2))
|
||||
print(c)
|
||||
|
||||
|
||||
# %%
|
||||
# write out in hdf5 format
|
||||
import h5py
|
||||
|
||||
fout_init = h5py.File('test_model_init.h5', 'w')
|
||||
fout_true = h5py.File('test_model_true.h5', 'w')
|
||||
|
||||
# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
|
||||
fout_init.create_dataset('eta', data=eta_init)
|
||||
fout_init.create_dataset('xi', data=xi_init)
|
||||
fout_init.create_dataset('zeta', data=zeta_init)
|
||||
fout_init.create_dataset('vel', data=vel_init)
|
||||
|
||||
# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
|
||||
fout_true.create_dataset('eta', data=eta_true)
|
||||
fout_true.create_dataset('xi', data=xi_true)
|
||||
fout_true.create_dataset('zeta', data=zeta_true)
|
||||
fout_true.create_dataset('vel', data=vel_true)
|
||||
|
||||
fout_init.close()
|
||||
fout_true.close()
|
||||
|
||||
|
||||
# %% [markdown]
|
||||
# # prepare src station file
|
||||
#
|
||||
# The following code creates a src_rec_file for the inversion, which describes the source and receiver positions and arrival times.
|
||||
# Format is as follows:
|
||||
#
|
||||
# ```
|
||||
# 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event
|
||||
# 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec
|
||||
# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
|
||||
# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
|
||||
# ....
|
||||
#
|
||||
# ```
|
||||
|
||||
# %%
|
||||
import random
|
||||
random.seed(1145141919810)
|
||||
|
||||
# dummys
|
||||
year_dummy = 1998
|
||||
month_dummy = 1
|
||||
day_dummy = 1
|
||||
hour_dummy = 0
|
||||
minute_dummy = 0
|
||||
second_dummy = 0
|
||||
mag_dummy = 3.0
|
||||
id_dummy = 1000
|
||||
st_name_dummy = 'AAAA'
|
||||
phase_dummy = 'P'
|
||||
arriv_t_dummy = 0.0
|
||||
|
||||
tt1deg = tt1 * 180.0/math.pi
|
||||
tt2deg = tt2 * 180.0/math.pi
|
||||
pp1deg = pp1 * 180.0/math.pi
|
||||
pp2deg = pp2 * 180.0/math.pi
|
||||
|
||||
|
||||
n_srcs = 8 # source will be placed around the domain
|
||||
r_src = 15 # radius of the source in degree
|
||||
|
||||
lines = []
|
||||
|
||||
#nij_rec = math.sqrt(n_rec[0])
|
||||
|
||||
pos_src=[]
|
||||
#pos_rec=[]
|
||||
|
||||
# center of the domain
|
||||
lon_c = (pp1deg+pp2deg)/2.0
|
||||
lat_c = (tt1deg+tt2deg)/2.0
|
||||
|
||||
# step of angle in degree = 360.0/n_srcs
|
||||
d_deg = 360.0/n_srcs
|
||||
|
||||
for i_src in range(n_srcs):
|
||||
|
||||
i_deg = i_src*d_deg
|
||||
lon = lon_c + r_src*math.cos(i_deg/180.0*math.pi)
|
||||
lat = lat_c + r_src*math.sin(i_deg/180.0*math.pi)
|
||||
# depth of the source
|
||||
dep = 10.0 + 0.5*i_src
|
||||
|
||||
src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, 0, id_dummy]
|
||||
lines.append(src)
|
||||
|
||||
pos_src.append([lon,lat,dep])
|
||||
|
||||
|
||||
# write out ev_arrivals file
|
||||
fname = 'src_only_test.dat'
|
||||
|
||||
with open(fname, 'w') as f:
|
||||
for line in lines:
|
||||
for elem in line:
|
||||
f.write('{} '.format(elem))
|
||||
f.write('\n')
|
||||
|
||||
|
||||
# %%
|
||||
# draw src and rec positions
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
for i_src in range(n_srcs):
|
||||
plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
|
||||
|
||||
# %%
|
||||
# plot receivers
|
||||
#for i_rec in range(n_rec[0]):
|
||||
# plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
|
||||
|
||||
# %%
|
||||
|
||||
|
||||
|
||||
98
test/old_tests/solver_performance/analysis_iter.ipynb
Normal file
98
test/old_tests/solver_performance/analysis_iter.ipynb
Normal file
File diff suppressed because one or more lines are too long
126
test/old_tests/solver_performance/check_3d_out.ipynb
Normal file
126
test/old_tests/solver_performance/check_3d_out.ipynb
Normal file
File diff suppressed because one or more lines are too long
145
test/old_tests/solver_performance/check_src_rec_file.ipynb
Normal file
145
test/old_tests/solver_performance/check_src_rec_file.ipynb
Normal file
@@ -0,0 +1,145 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# read src_rec file and check its arrival time and distance from src to rec\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"# read file\n",
|
||||
"fpath = \"./src_rec_test_out.dat\"\n",
|
||||
"\n",
|
||||
"with open(fpath, \"r\") as f:\n",
|
||||
" lines = f.readlines()\n",
|
||||
"\n",
|
||||
" # list to store src lon lat\n",
|
||||
" src_pos = []\n",
|
||||
" # list to store rec lon lat\n",
|
||||
" rec_pos_tmp=[]\n",
|
||||
" rec_pos = []\n",
|
||||
"\n",
|
||||
" for line in lines:\n",
|
||||
" # src line if there are 13 elements\n",
|
||||
" if len(line.split()) == 13:\n",
|
||||
" # store source lon lat dep\n",
|
||||
" stlon = float(line.split()[8])\n",
|
||||
" stlat = float(line.split()[7])\n",
|
||||
" src_pos.append([stlon, stlat])\n",
|
||||
"\n",
|
||||
" nrec = float(line.split()[11])\n",
|
||||
" # rec line if there are 9 elements\n",
|
||||
" elif len(line.split()) == 9:\n",
|
||||
" # store receiver lon lat dep\n",
|
||||
" rclon = float(line.split()[4])\n",
|
||||
" rclat = float(line.split()[3])\n",
|
||||
" rctime= float(line.split()[8])\n",
|
||||
" # calc epicentral distance from src\n",
|
||||
" dist = np.sqrt((stlon-rclon)**2 + (stlat-rclat)**2)\n",
|
||||
" rec_pos_tmp.append([rclon, rclat, rctime, dist])\n",
|
||||
"\n",
|
||||
" nrec-=1\n",
|
||||
" else:\n",
|
||||
" raise ValueError(\"src_rec_test_out.dat file is not correct\")\n",
|
||||
"\n",
|
||||
" if nrec==0:\n",
|
||||
" rec_pos.append(rec_pos_tmp)\n",
|
||||
" # remove all rec_pos_tmp\n",
|
||||
" rec_pos_tmp = []\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"src_pos = np.array(src_pos)\n",
|
||||
"rec_pos = np.array(rec_pos)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot rec_pos for each src_pos with color by 3rd element\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"# selected source\n",
|
||||
"id_src = 0\n",
|
||||
"\n",
|
||||
"fig, axs = plt.subplots(2,1,figsize=(10,10))\n",
|
||||
"\n",
|
||||
"# plot arrival time\n",
|
||||
"# src\n",
|
||||
"axs[0].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
"# rec\n",
|
||||
"axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=10, marker='o')\n",
|
||||
"\n",
|
||||
"# colorbar\n",
|
||||
"cbar = plt.colorbar(axs[0].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,2], s=10, marker='o'))\n",
|
||||
"cbar.set_label('arrival time')\n",
|
||||
"\n",
|
||||
"# plot epicentral distance\n",
|
||||
"# src\n",
|
||||
"axs[1].scatter(src_pos[id_src,0], src_pos[id_src,1], c='r', marker='o', s=100)\n",
|
||||
"# rec\n",
|
||||
"\n",
|
||||
"axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=10, marker='o')\n",
|
||||
"\n",
|
||||
"# colorbar\n",
|
||||
"cbar = plt.colorbar(axs[1].scatter(rec_pos[id_src][:,0], rec_pos[id_src][:,1], c=rec_pos[id_src][:,3], s=10, marker='o'))\n",
|
||||
"cbar.set_label('epicentral distance')\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"rec_pos.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"min(rec_pos[id_src][:,2])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"interpreter": {
|
||||
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
59
test/old_tests/solver_performance/iter.txt
Normal file
59
test/old_tests/solver_performance/iter.txt
Normal file
@@ -0,0 +1,59 @@
|
||||
iteration 0: 2.68606, 6.23229, 0.226239
|
||||
iteration 1: 2.66762, 4.63719, 0.214316
|
||||
iteration 2: 2.73238, 4.08102, 0.213379
|
||||
iteration 3: 2.77977, 4.02757, 0.215531
|
||||
iteration 4: 2.75503, 3.96133, 0.213489
|
||||
iteration 5: 2.70629, 3.89322, 0.215038
|
||||
iteration 6: 2.64874, 3.82701, 0.228276
|
||||
iteration 7: 2.58487, 3.76405, 0.212526
|
||||
iteration 8: 2.5151, 3.70497, 0.210962
|
||||
iteration 9: 2.43957, 3.65005, 0.212779
|
||||
iteration 10: 2.35845, 3.59922, 0.215859
|
||||
iteration 11: 2.27194, 3.55211, 0.218057
|
||||
iteration 12: 2.18033, 3.50805, 0.223463
|
||||
iteration 13: 2.08403, 3.46617, 0.218698
|
||||
iteration 14: 1.98362, 3.42552, 0.215489
|
||||
iteration 15: 1.87984, 3.38526, 0.21415
|
||||
iteration 16: 1.77353, 3.34488, 0.211472
|
||||
iteration 17: 1.66557, 3.30434, 0.214
|
||||
iteration 18: 1.55685, 3.26406, 0.221782
|
||||
iteration 19: 1.44815, 3.22471, 0.21206
|
||||
iteration 20: 1.34022, 3.18704, 0.216203
|
||||
iteration 21: 1.23371, 3.15168, 0.212569
|
||||
iteration 22: 1.12917, 3.11898, 0.213464
|
||||
iteration 23: 1.02721, 3.08897, 0.213914
|
||||
iteration 24: 0.928483, 3.06131, 0.214082
|
||||
iteration 25: 0.833576, 3.03521, 0.214501
|
||||
iteration 26: 0.742987, 3.00939, 0.213422
|
||||
iteration 27: 0.657363, 2.98204, 0.221331
|
||||
iteration 28: 0.577238, 2.95076, 0.215693
|
||||
iteration 29: 0.502953, 2.9126, 0.223062
|
||||
iteration 30: 0.434765, 2.86425, 0.217287
|
||||
iteration 31: 0.372809, 2.811, 0.22508
|
||||
iteration 32: 0.317086, 2.74301, 0.213147
|
||||
iteration 33: 0.267455, 2.65645, 0.213563
|
||||
iteration 34: 0.223675, 2.55053, 0.214785
|
||||
iteration 35: 0.185412, 2.42585, 0.214462
|
||||
iteration 36: 0.152346, 2.28442, 0.213213
|
||||
iteration 37: 0.124075, 2.12939, 0.215673
|
||||
iteration 38: 0.100158, 1.96561, 0.214523
|
||||
iteration 39: 0.080066, 1.76634, 0.213322
|
||||
iteration 40: 0.0633697, 1.58065, 0.248635
|
||||
iteration 41: 0.0496571, 1.41768, 0.227537
|
||||
iteration 42: 0.0385206, 1.26136, 0.214846
|
||||
iteration 43: 0.0295813, 1.06553, 0.212869
|
||||
iteration 44: 0.0224539, 0.922364, 0.215505
|
||||
iteration 45: 0.0168533, 0.801121, 0.215831
|
||||
iteration 46: 0.012518, 0.676654, 0.222596
|
||||
iteration 47: 0.00919207, 0.572065, 0.212897
|
||||
iteration 48: 0.00666999, 0.473973, 0.215161
|
||||
iteration 49: 0.00478044, 0.388867, 0.214475
|
||||
iteration 50: 0.00338263, 0.313598, 0.212979
|
||||
iteration 51: 0.00236278, 0.246673, 0.213896
|
||||
iteration 52: 0.00162948, 0.185409, 0.216258
|
||||
iteration 53: 0.00111072, 0.122625, 0.220116
|
||||
iteration 54: 0.000747838, 0.0897312, 0.214795
|
||||
iteration 55: 0.000496874, 0.0652654, 0.214746
|
||||
iteration 56: 0.000325716, 0.0467522, 0.214539
|
||||
iteration 57: 0.000210643, 0.0329173, 0.222138
|
||||
iteration 58: 0.000134388, 0.0227652, 0.216016
|
||||
100
test/old_tests/solver_performance/iter_cuda.txt
Normal file
100
test/old_tests/solver_performance/iter_cuda.txt
Normal file
@@ -0,0 +1,100 @@
|
||||
iteration 0: 2.43339, 3.96179, 0.159862
|
||||
iteration 1: 2.44192, 3.78108, 0.154897
|
||||
iteration 2: 2.5263, 3.76444, 0.154628
|
||||
iteration 3: 2.63063, 3.75984, 0.155039
|
||||
iteration 4: 2.67147, 3.74936, 0.154697
|
||||
iteration 5: 2.69534, 3.72929, 0.15431
|
||||
iteration 6: 2.71752, 3.70022, 0.153941
|
||||
iteration 7: 2.73461, 3.70193, 0.153911
|
||||
iteration 8: 2.739, 3.95594, 0.152974
|
||||
iteration 9: 2.72188, 4.19984, 0.153161
|
||||
iteration 10: 2.67363, 4.43216, 0.153304
|
||||
iteration 11: 2.5887, 4.64604, 0.153101
|
||||
iteration 12: 2.46947, 4.72927, 0.152961
|
||||
iteration 13: 2.32484, 4.78864, 0.153142
|
||||
iteration 14: 2.16648, 4.85847, 0.152842
|
||||
iteration 15: 2.00464, 4.78123, 0.152974
|
||||
iteration 16: 1.84584, 4.55547, 0.153136
|
||||
iteration 17: 1.69311, 4.41426, 0.153256
|
||||
iteration 18: 1.54733, 4.18296, 0.152845
|
||||
iteration 19: 1.40845, 4.0995, 0.153227
|
||||
iteration 20: 1.27643, 4.03077, 0.152958
|
||||
iteration 21: 1.15168, 3.96649, 0.152978
|
||||
iteration 22: 1.03503, 3.90766, 0.153147
|
||||
iteration 23: 0.927456, 3.87121, 0.153028
|
||||
iteration 24: 0.829742, 3.77373, 0.15331
|
||||
iteration 25: 0.742219, 3.6127, 0.153352
|
||||
iteration 26: 0.664713, 3.40771, 0.153238
|
||||
iteration 27: 0.596583, 3.17937, 0.152994
|
||||
iteration 28: 0.536932, 2.9447, 0.153596
|
||||
iteration 29: 0.484754, 2.71571, 0.153629
|
||||
iteration 30: 0.439041, 2.49966, 0.15342
|
||||
iteration 31: 0.398856, 2.30025, 0.153487
|
||||
iteration 32: 0.363395, 2.11871, 0.153484
|
||||
iteration 33: 0.331981, 1.95478, 0.153198
|
||||
iteration 34: 0.304034, 1.80739, 0.152914
|
||||
iteration 35: 0.27906, 1.67506, 0.153539
|
||||
iteration 36: 0.256656, 1.55623, 0.152955
|
||||
iteration 37: 0.236486, 1.44935, 0.153024
|
||||
iteration 38: 0.218247, 1.35301, 0.153084
|
||||
iteration 39: 0.201717, 1.26594, 0.15378
|
||||
iteration 40: 0.186682, 1.187, 0.154371
|
||||
iteration 41: 0.172982, 1.11523, 0.15392
|
||||
iteration 42: 0.16048, 1.04978, 0.153982
|
||||
iteration 43: 0.14905, 0.989915, 0.153204
|
||||
iteration 44: 0.138585, 0.924638, 0.153238
|
||||
iteration 45: 0.128997, 0.856952, 0.153877
|
||||
iteration 46: 0.120206, 0.810159, 0.152934
|
||||
iteration 47: 0.112133, 0.767564, 0.152937
|
||||
iteration 48: 0.104707, 0.728427, 0.153035
|
||||
iteration 49: 0.097869, 0.692264, 0.15315
|
||||
iteration 50: 0.0915679, 0.658715, 0.152971
|
||||
iteration 51: 0.0857542, 0.6275, 0.153151
|
||||
iteration 52: 0.0803839, 0.598383, 0.153117
|
||||
iteration 53: 0.075418, 0.571163, 0.153092
|
||||
iteration 54: 0.0708228, 0.545663, 0.153108
|
||||
iteration 55: 0.0665671, 0.521722, 0.152929
|
||||
iteration 56: 0.0626222, 0.499192, 0.153113
|
||||
iteration 57: 0.0589632, 0.477937, 0.15294
|
||||
iteration 58: 0.0555681, 0.457812, 0.15317
|
||||
iteration 59: 0.0524166, 0.440694, 0.153242
|
||||
iteration 60: 0.0494894, 0.420541, 0.153075
|
||||
iteration 61: 0.046768, 0.400276, 0.152928
|
||||
iteration 62: 0.0442361, 0.383639, 0.153059
|
||||
iteration 63: 0.0418792, 0.368117, 0.153116
|
||||
iteration 64: 0.0396837, 0.353607, 0.153163
|
||||
iteration 65: 0.0376369, 0.339252, 0.152713
|
||||
iteration 66: 0.0357276, 0.324887, 0.152917
|
||||
iteration 67: 0.0339456, 0.312162, 0.153061
|
||||
iteration 68: 0.0322809, 0.300005, 0.153249
|
||||
iteration 69: 0.0307245, 0.288393, 0.153127
|
||||
iteration 70: 0.0292682, 0.277323, 0.153116
|
||||
iteration 71: 0.0279043, 0.266659, 0.153007
|
||||
iteration 72: 0.026626, 0.256528, 0.152774
|
||||
iteration 73: 0.0254269, 0.246895, 0.152918
|
||||
iteration 74: 0.0243012, 0.237501, 0.153007
|
||||
iteration 75: 0.0232433, 0.228719, 0.153019
|
||||
iteration 76: 0.0222484, 0.219205, 0.152934
|
||||
iteration 77: 0.0213118, 0.203637, 0.153179
|
||||
iteration 78: 0.0204296, 0.195446, 0.152973
|
||||
iteration 79: 0.0195979, 0.187844, 0.152942
|
||||
iteration 80: 0.0188131, 0.180718, 0.152817
|
||||
iteration 81: 0.0180721, 0.174, 0.15292
|
||||
iteration 82: 0.0173716, 0.167641, 0.152875
|
||||
iteration 83: 0.0167088, 0.161606, 0.153251
|
||||
iteration 84: 0.016081, 0.155857, 0.152889
|
||||
iteration 85: 0.0154857, 0.150374, 0.153223
|
||||
iteration 86: 0.0149207, 0.145136, 0.153109
|
||||
iteration 87: 0.014384, 0.140125, 0.153087
|
||||
iteration 88: 0.0138737, 0.135328, 0.152957
|
||||
iteration 89: 0.0133879, 0.130732, 0.152905
|
||||
iteration 90: 0.0129251, 0.126323, 0.153395
|
||||
iteration 91: 0.0124838, 0.122094, 0.153812
|
||||
iteration 92: 0.0120626, 0.118033, 0.153761
|
||||
iteration 93: 0.0116603, 0.114132, 0.153533
|
||||
iteration 94: 0.0112756, 0.110382, 0.153376
|
||||
iteration 95: 0.0109075, 0.106777, 0.153344
|
||||
iteration 96: 0.010555, 0.103309, 0.153178
|
||||
iteration 97: 0.0102171, 0.0999714, 0.153041
|
||||
iteration 98: 0.00989304, 0.0967585, 0.153617
|
||||
iteration 99: 0.00958196, 0.0936645, 0.153021
|
||||
478
test/old_tests/solver_performance/log_val
Normal file
478
test/old_tests/solver_performance/log_val
Normal file
@@ -0,0 +1,478 @@
|
||||
==24162== Memcheck, a memory error detector
|
||||
==24162== Copyright (C) 2002-2017, and GNU GPL'd, by Julian Seward et al.
|
||||
==24162== Using Valgrind-3.18.1 and LibVEX; rerun with -h for copyright info
|
||||
==24162== Command: ../../build/TOMOATT -i input_params_100-100-100_1-1-1-1_gpu.yml
|
||||
==24162== Parent PID: 24158
|
||||
==24162==
|
||||
==24162== Warning: noted but unhandled ioctl 0x30000001 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x27 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x25 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x37 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x17 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: set address range perms: large range [0x200000000, 0x300200000) (noaccess)
|
||||
==24162== Warning: set address range perms: large range [0x8fa5000, 0x28fa4000) (noaccess)
|
||||
==24162== Warning: noted but unhandled ioctl 0x19 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: set address range perms: large range [0x10006000000, 0x10106000000) (noaccess)
|
||||
==24162== Warning: noted but unhandled ioctl 0x49 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x21 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x1b with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: noted but unhandled ioctl 0x44 with no size/direction hints.
|
||||
==24162== This could cause spurious value errors to appear.
|
||||
==24162== See README_MISSING_SYSCALL_OR_IOCTL for guidance on writing a proper wrapper.
|
||||
==24162== Warning: set address range perms: large range [0x10006000000, 0x10106000000) (noaccess)
|
||||
==24162==
|
||||
==24162== HEAP SUMMARY:
|
||||
==24162== in use at exit: 1,079,727 bytes in 174 blocks
|
||||
==24162== total heap usage: 108,062 allocs, 107,888 frees, 2,182,558,459 bytes allocated
|
||||
==24162==
|
||||
==24162== 1 bytes in 1 blocks are definitely lost in loss record 1 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x53C960E: strdup (strdup.c:42)
|
||||
==24162== by 0x75E2534: ???
|
||||
==24162== by 0x75DB373: ???
|
||||
==24162== by 0x568F61F: mca_base_framework_components_register (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x568F9B5: mca_base_framework_register (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x568FA13: mca_base_framework_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x503CBD3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 5 bytes in 1 blocks are definitely lost in loss record 4 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x53C960E: strdup (strdup.c:42)
|
||||
==24162== by 0x5690090: opal_argv_append_nosize (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x56901B8: opal_argv_append (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x5690351: opal_argv_split_inter (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75F3FA7: ???
|
||||
==24162== by 0x75F5B26: ???
|
||||
==24162== by 0x56A76B1: mca_btl_base_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75C91B7: ???
|
||||
==24162== by 0x4FED533: mca_bml_base_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CBB3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162==
|
||||
==24162== 8 bytes in 1 blocks are definitely lost in loss record 8 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x56A9469: dlopen_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75A955F: ???
|
||||
==24162== by 0x75D434D: ???
|
||||
==24162== by 0x56A76B1: mca_btl_base_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75C91B7: ???
|
||||
==24162== by 0x4FED533: mca_bml_base_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CBB3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 8 bytes in 1 blocks are definitely lost in loss record 9 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x56A9469: dlopen_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75A955F: ???
|
||||
==24162== by 0x75F5834: ???
|
||||
==24162== by 0x56A76B1: mca_btl_base_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75C91B7: ???
|
||||
==24162== by 0x4FED533: mca_bml_base_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CBB3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 13 bytes in 1 blocks are definitely lost in loss record 10 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x53C960E: strdup (strdup.c:42)
|
||||
==24162== by 0x75A95EC: ???
|
||||
==24162== by 0x75D434D: ???
|
||||
==24162== by 0x56A76B1: mca_btl_base_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75C91B7: ???
|
||||
==24162== by 0x4FED533: mca_bml_base_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CBB3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 13 bytes in 1 blocks are definitely lost in loss record 11 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x53C960E: strdup (strdup.c:42)
|
||||
==24162== by 0x75A95EC: ???
|
||||
==24162== by 0x75F5834: ???
|
||||
==24162== by 0x56A76B1: mca_btl_base_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x75C91B7: ???
|
||||
==24162== by 0x4FED533: mca_bml_base_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CBB3: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 72 bytes in 1 blocks are possibly lost in loss record 59 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x79BE805: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7893A0A: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC07B9: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162==
|
||||
==24162== 72 bytes in 1 blocks are possibly lost in loss record 60 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x7890E34: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7892B41: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78932B9: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC12D7: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162==
|
||||
==24162== 79 (64 direct, 15 indirect) bytes in 1 blocks are definitely lost in loss record 61 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x75C117A: ???
|
||||
==24162== by 0x568544E: mca_base_framework_components_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x56F3E45: mca_mpool_base_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x568FA88: mca_base_framework_open (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libopen-pal.so.40.30.2)
|
||||
==24162== by 0x503CB74: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 93 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC044A: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162== by 0x1FECA9: main (main.cpp:42)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 94 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0479: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162== by 0x1FECA9: main (main.cpp:42)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 95 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A12519: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A1264D: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A00E5B: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0827: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 96 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A12519: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A1264D: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7A00E81: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0827: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 97 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0C01: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162== by 0x1FECA9: main (main.cpp:42)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 98 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7893021: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78932D4: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC12D7: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 99 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0CB2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162== by 0x1FECA9: main (main.cpp:42)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 100 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0D4C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162== by 0x1FECA9: main (main.cpp:42)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 101 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x799F135: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0DC7: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 102 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x799F155: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0DC7: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162==
|
||||
==24162== 152 bytes in 1 blocks are possibly lost in loss record 103 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x794043C: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x799F175: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC0DC7: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2C8370: cudaGetDeviceCount (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x1FE548: initialize_cuda() (cuda_initialize.cuh:39)
|
||||
==24162==
|
||||
==24162== 320 bytes in 1 blocks are possibly lost in loss record 114 of 151
|
||||
==24162== at 0x484DA83: calloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x40147D9: calloc (rtld-malloc.h:44)
|
||||
==24162== by 0x40147D9: allocate_dtv (dl-tls.c:375)
|
||||
==24162== by 0x40147D9: _dl_allocate_tls (dl-tls.c:634)
|
||||
==24162== by 0x53B6834: allocate_stack (allocatestack.c:430)
|
||||
==24162== by 0x53B6834: pthread_create@@GLIBC_2.34 (pthread_create.c:647)
|
||||
==24162== by 0x789EC26: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x794C75E: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x7AC1A49: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x78AAAA2: ??? (in /usr/lib/x86_64-linux-gnu/libcuda.so.515.65.01)
|
||||
==24162== by 0x2A8482: __cudart516 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x2A8547: __cudart1336 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x53BAF67: __pthread_once_slow (pthread_once.c:116)
|
||||
==24162== by 0x2F6AE8: __cudart1612 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162== by 0x29F0E6: __cudart514 (in /home/masarunagaso/workspace/TomoATT/build/TOMOATT)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 122 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EAB3: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 123 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EAB3: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 124 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EB7A: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 125 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EB7A: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 126 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EC26: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 127 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EC26: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 128 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9ECD4: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 129 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9ECD4: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 130 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EE36: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 131 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EE36: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 132 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EF96: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 133 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9EF96: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 134 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x502A9B6: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9F0F4: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== 688 bytes in 1 blocks are definitely lost in loss record 135 of 151
|
||||
==24162== at 0x4848899: malloc (in /usr/libexec/valgrind/vgpreload_memcheck-amd64-linux.so)
|
||||
==24162== by 0x756D41B: ???
|
||||
==24162== by 0x502ACAE: ompi_op_base_op_select (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4F9F0F4: ompi_op_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x503CB0D: ompi_mpi_init (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x4FD0878: PMPI_Init_thread (in /home/masarunagaso/workspace/TomoATT/external_libs/local_mpi_hdf5/lib/libmpi.so.40.30.3)
|
||||
==24162== by 0x20EE52: initialize_mpi() (mpi_funcs.h:68)
|
||||
==24162== by 0x1FEC1D: main (main.cpp:28)
|
||||
==24162==
|
||||
==24162== LEAK SUMMARY:
|
||||
==24162== definitely lost: 9,744 bytes in 21 blocks
|
||||
==24162== indirectly lost: 15 bytes in 1 blocks
|
||||
==24162== possibly lost: 2,136 bytes in 14 blocks
|
||||
==24162== still reachable: 1,067,832 bytes in 138 blocks
|
||||
==24162== suppressed: 0 bytes in 0 blocks
|
||||
==24162== Reachable blocks (those to which a pointer was found) are not shown.
|
||||
==24162== To see them, rerun with: --leak-check=full --show-leak-kinds=all
|
||||
==24162==
|
||||
==24162== For lists of detected and suppressed errors, rerun with: -s
|
||||
==24162== ERROR SUMMARY: 35 errors from 35 contexts (suppressed: 0 from 0)
|
||||
298
test/old_tests/solver_performance/make_test_model.py
Normal file
298
test/old_tests/solver_performance/make_test_model.py
Normal file
@@ -0,0 +1,298 @@
|
||||
# %% [markdown]
|
||||
# # notebook for create init and true test model
|
||||
|
||||
# %%
|
||||
import numpy as np
|
||||
import math
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
# get arguments
|
||||
import argparse
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--n_rtp", type=int, nargs=3, default=[55,55,55])
|
||||
# n_sweep
|
||||
parser.add_argument("--n_sweep", type=int, default=1)
|
||||
# ndiv_rtp
|
||||
parser.add_argument("--ndiv_rtp", type=int, nargs=3, default=[1,1,1])
|
||||
# use_gpu
|
||||
parser.add_argument("--use_gpu", type=int, default=0)
|
||||
|
||||
|
||||
n_rtp = parser.parse_args().n_rtp
|
||||
n_sweep = parser.parse_args().n_sweep
|
||||
ndiv_rtp = parser.parse_args().ndiv_rtp
|
||||
use_gpu = parser.parse_args().use_gpu
|
||||
|
||||
#
|
||||
# create model file if not exists
|
||||
#
|
||||
|
||||
# filename
|
||||
str_nrtp = str(n_rtp[0])+"-"+str(n_rtp[1])+"-"+str(n_rtp[2])
|
||||
fname_init = 'test_model_init_{}.h5'.format(str_nrtp)
|
||||
fname_true = 'test_model_true_{}.h5'.format(str_nrtp)
|
||||
|
||||
# grid params
|
||||
R_earth = 6371.0 #6378.1370
|
||||
rr1=6070
|
||||
rr2=6400
|
||||
tt1=(30.0-1.5)/180*math.pi
|
||||
tt2=(50.0+1.5)/180*math.pi
|
||||
pp1=(15.0-1.5)/180*math.pi
|
||||
pp2=(40.0+1.5)/180*math.pi
|
||||
|
||||
import os
|
||||
if not os.path.exists(fname_true):
|
||||
|
||||
#n_rtp = [55,55,55]
|
||||
dr = (rr2-rr1)/(n_rtp[0]-1)
|
||||
dt = (tt2-tt1)/(n_rtp[1]-1)
|
||||
dp = (pp2-pp1)/(n_rtp[2]-1)
|
||||
rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])
|
||||
tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
|
||||
pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])
|
||||
|
||||
# initial model
|
||||
gamma = 0.0
|
||||
#s0 = 1.0/6.0
|
||||
slow_p=0.04
|
||||
ani_p=0.03
|
||||
|
||||
eta_init = np.zeros(n_rtp)
|
||||
xi_init = np.zeros(n_rtp)
|
||||
zeta_init = np.zeros(n_rtp)
|
||||
fun_init = np.zeros(n_rtp)
|
||||
vel_init = np.zeros(n_rtp)
|
||||
|
||||
# true model
|
||||
eta_true = np.zeros(n_rtp)
|
||||
xi_true = np.zeros(n_rtp)
|
||||
zeta_true = np.zeros(n_rtp)
|
||||
fun_true = np.zeros(n_rtp)
|
||||
vel_true = np.zeros(n_rtp)
|
||||
|
||||
c=0
|
||||
for ir in range(n_rtp[2]):
|
||||
for it in range(n_rtp[1]):
|
||||
for ip in range(n_rtp[0]):
|
||||
#eta_init[ir,it,ip] = 0.0
|
||||
#xi_init[ir,it,ip] = 0.0
|
||||
zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)
|
||||
|
||||
if (rr[ir]>6351):
|
||||
fun_init[ir,it,ip] = 1.0/(5.8+(6371-rr[ir])/20.0*0.7)
|
||||
elif (rr[ir]>6336):
|
||||
fun_init[ir,it,ip] = 1.0/(6.5+(6351-rr[ir])/15.0*0.6)
|
||||
elif (rr[ir]>5961):
|
||||
fun_init[ir,it,ip] = 1.0/(8.0+(6336-rr[ir])/375.0*1)
|
||||
else:
|
||||
fun_init[ir,it,ip] = 1.0/9.0
|
||||
|
||||
vel_init[ir,it,ip] = 1.0/fun_init[ir,it,ip]
|
||||
|
||||
# true model
|
||||
if (tt[it] >= 30.0/180.0*math.pi and tt[it] <= 50.0/180.0*math.pi \
|
||||
and pp[ip] >= 15.0/180.0*math.pi and pp[ip] <= 40.0/180.0*math.pi \
|
||||
and rr[ir] >= 6211.0 and rr[ir] <= 6371.0):
|
||||
c+=1
|
||||
sigma = math.sin(4.0*math.pi*(tt[it]-30.0/180.0*math.pi)/(20.0/180.0*math.pi)) \
|
||||
*math.sin(4.0*math.pi*(pp[ip]-15.0/180.0*math.pi)/(25.0/180.0*math.pi)) \
|
||||
*math.sin(2.0*math.pi*(rr[ir]-6211.0)/160.0)
|
||||
else:
|
||||
sigma = 0.0
|
||||
|
||||
if sigma < 0:
|
||||
psi = 60.0/180.0*math.pi
|
||||
elif sigma > 0:
|
||||
psi = 150.0/180.0*math.pi
|
||||
else:
|
||||
psi = 0.0
|
||||
|
||||
eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)
|
||||
xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)
|
||||
zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)
|
||||
fun_true[ir,it,ip] = fun_init[ir,it,ip]/(1.0+sigma*slow_p)
|
||||
vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip]
|
||||
|
||||
|
||||
|
||||
r_earth = R_earth #6378.1370
|
||||
print("depminmax {} {}".format(r_earth-rr1,r_earth-rr2))
|
||||
print(c)
|
||||
|
||||
|
||||
# %%
|
||||
# write out
|
||||
import h5py
|
||||
|
||||
# n_rtp to storing
|
||||
fout_init = h5py.File(fname_init, 'w')
|
||||
fout_true = h5py.File(fname_true, 'w')
|
||||
|
||||
# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
|
||||
fout_init.create_dataset('eta', data=eta_init)
|
||||
fout_init.create_dataset('xi', data=xi_init)
|
||||
fout_init.create_dataset('zeta',data=zeta_init)
|
||||
fout_init.create_dataset('vel', data=vel_init)
|
||||
|
||||
# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
|
||||
fout_true.create_dataset('eta', data=eta_true)
|
||||
fout_true.create_dataset('xi', data=xi_true)
|
||||
fout_true.create_dataset('zeta',data=zeta_true)
|
||||
fout_true.create_dataset('vel', data=vel_true)
|
||||
|
||||
fout_init.close()
|
||||
fout_true.close()
|
||||
|
||||
#
|
||||
# create src rec file
|
||||
|
||||
# %% [markdown]
|
||||
# # prepare src station file
|
||||
#
|
||||
# ```
|
||||
# 26 1992 1 1 2 43 56.900 1.8000 98.9000 137.00 2.80 8 305644 <- src : id_src year month day hour min sec lat lon dep_km mag num_recs id_event
|
||||
# 26 1 PCBI 1.8900 98.9253 1000.0000 P 10.40 18.000 <- arrival : id_src id_rec name_rec lat lon elevation_m phase epicentral_distance_km arrival_time_sec
|
||||
# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
|
||||
# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
|
||||
#
|
||||
# ```
|
||||
|
||||
# %%
|
||||
#import random
|
||||
#random.seed(123456789)
|
||||
|
||||
# dummys
|
||||
year_dummy = 1998
|
||||
month_dummy = 1
|
||||
day_dummy = 1
|
||||
hour_dummy = 0
|
||||
minute_dummy = 0
|
||||
second_dummy = 0
|
||||
mag_dummy = 3.0
|
||||
id_dummy = 1000
|
||||
st_name_dummy = 'AAAA'
|
||||
phase_dummy = 'P'
|
||||
arriv_t_dummy = 0.0
|
||||
|
||||
tt1deg = tt1 * 180.0/math.pi
|
||||
tt2deg = tt2 * 180.0/math.pi
|
||||
pp1deg = pp1 * 180.0/math.pi
|
||||
pp2deg = pp2 * 180.0/math.pi
|
||||
|
||||
|
||||
n_src = 1
|
||||
n_rec = [1 for x in range(n_src)]
|
||||
|
||||
|
||||
lines = []
|
||||
|
||||
pos_src=[]
|
||||
pos_rec=[]
|
||||
|
||||
dep_srcs=[12.902894]
|
||||
lon_srcs=[16.794572]
|
||||
lat_srcs=[37.503373]
|
||||
|
||||
elev_recs = [0.0]
|
||||
lon_recs = [29.812050]
|
||||
lat_recs = [36.472809]
|
||||
|
||||
|
||||
# create dummy src
|
||||
for i_src in range(n_src):
|
||||
# define one point in the domain (rr1 bottom, rr2 top)
|
||||
dep = dep_srcs[i_src]
|
||||
lon = lon_srcs[i_src]
|
||||
lat = lat_srcs[i_src]
|
||||
|
||||
src = [i_src, year_dummy, month_dummy, day_dummy, hour_dummy, minute_dummy, second_dummy, lat, lon, dep, mag_dummy, n_rec[i_src], id_dummy]
|
||||
lines.append(src)
|
||||
|
||||
pos_src.append([lon,lat,dep])
|
||||
|
||||
# create dummy station
|
||||
for i_rec in range(n_rec[i_src]):
|
||||
#elev_rec = random.uniform(0.0,-10.0) # elevation in m
|
||||
#lon_rec = random.uniform(pp1deg,pp2deg)
|
||||
#lat_rec = random.uniform(tt1deg,tt2deg)
|
||||
|
||||
rec = [i_src, i_rec, st_name_dummy+"_"+str(i_rec), lat_recs[i_rec], lon_recs[i_rec], elev_recs[i_rec], phase_dummy, arriv_t_dummy]
|
||||
lines.append(rec)
|
||||
|
||||
pos_rec.append([lon_recs[i_rec],lat_recs[i_rec],elev_recs[i_rec]])
|
||||
|
||||
# write out ev_arrivals file
|
||||
fname = 'src_rec_test.dat'
|
||||
|
||||
with open(fname, 'w') as f:
|
||||
for line in lines:
|
||||
for elem in line:
|
||||
f.write('{} '.format(elem))
|
||||
f.write('\n')
|
||||
|
||||
|
||||
# %%
|
||||
# draw src and rec positions
|
||||
#import matplotlib.pyplot as plt
|
||||
#
|
||||
#for i_src in range(n_src):
|
||||
# plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
|
||||
#
|
||||
## %%
|
||||
## plot receivers
|
||||
#for i_rec in range(n_rec[0]):
|
||||
# plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
|
||||
|
||||
|
||||
str_input_file = """version : 2
|
||||
|
||||
domain :
|
||||
#min_max_dep : [-21.863,308.8137] # depth in km
|
||||
min_max_dep : [-29.0, 301.0] # depth in km with R = 6371.0
|
||||
min_max_lat : [28.5,51.5] # latitude in degree
|
||||
min_max_lon : [13.5,41.5] # longitude in degree
|
||||
n_rtp : [{},{},{}] # number of nodes
|
||||
|
||||
source :
|
||||
#src_dep_lat_lon : [5.0,40.0,24.0] # source depth in km, latitude, longitude in degree
|
||||
#src_dep_lat_lon : [5750.6370,46.0,36.0] # source depth in km, latitude, longitude in degree
|
||||
src_rec_file : 'src_rec_test.dat' # source receiver file (if found, src_dep_lat_lon is ignored)
|
||||
swap_src_rec : 1 # swap source and receiver
|
||||
|
||||
model :
|
||||
init_model_type : '' # 'fd' (input file) or '1d_ak135'
|
||||
init_model_path : './test_model_true_{}-{}-{}.h5' # path to initial model file (ignored if init_model_type is '1d_*')
|
||||
|
||||
inversion :
|
||||
run_mode : 0 # 0 for forward simulation only, 1 for inversion
|
||||
n_inversion_grid : 1
|
||||
|
||||
|
||||
parallel :
|
||||
n_sims : 1 # number of simultaneous run
|
||||
ndiv_rtp : [{},{},{}] # number of subdomains
|
||||
nproc_sub : {} # number of subprocess used for each subdomain
|
||||
use_gpu : {}
|
||||
|
||||
calculation :
|
||||
convergence_tolerance : 1e-4
|
||||
max_iterations : 200
|
||||
stencil_order : 3 # 1 or 3
|
||||
sweep_type : 1 # 0: legacy, 1: cuthill-mckee with shm parallelization
|
||||
|
||||
output_setting :
|
||||
is_output_source_field : 0 # output the calculated field of all sources 1 for yes; 0 for no; default: 1
|
||||
is_verbose_output : 0 # output internal parameters, if no, only model parameters are out. 1 for yes; 0 for no; default: 0
|
||||
is_output_model_dat : 0 # output model_parameters_inv_0000.dat or not. 1 for yes; 0 for no; default: 1
|
||||
|
||||
""".format(n_rtp[0],n_rtp[1],n_rtp[2],n_rtp[0],n_rtp[1],n_rtp[2], ndiv_rtp[0],ndiv_rtp[1],ndiv_rtp[2], n_sweep, use_gpu)
|
||||
|
||||
str_nsweep_ndiv_rtp = str(n_sweep) + '-' + str(ndiv_rtp[0]) + '-' + str(ndiv_rtp[1]) + '-' + str(ndiv_rtp[2])
|
||||
|
||||
# write out
|
||||
with open('input_params_{}_{}.yml'.format(str_nrtp, str_nsweep_ndiv_rtp), 'w') as f:
|
||||
f.write(str_input_file)
|
||||
|
||||
|
||||
163
test/old_tests/solver_performance/plot_SIMD_effect.ipynb
Normal file
163
test/old_tests/solver_performance/plot_SIMD_effect.ipynb
Normal file
File diff suppressed because one or more lines are too long
139
test/old_tests/solver_performance/pvpython_test.py
Normal file
139
test/old_tests/solver_performance/pvpython_test.py
Normal file
@@ -0,0 +1,139 @@
|
||||
from paraview.simple import *
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
# get args
|
||||
args = sys.argv
|
||||
if len(args) != 3:
|
||||
print("Usage: pvpython draw_slice.py <data_file> <dataset_name>")
|
||||
sys.exit(1)
|
||||
|
||||
# get data
|
||||
fpath = args[1]
|
||||
name_dset = args[2]
|
||||
|
||||
|
||||
#fpath = "OUTPUT_FILES/out_data_sim_0.xmf"
|
||||
#name_dset = 'fun_inv_0000'
|
||||
|
||||
# create a new 'XDMF Reader'
|
||||
out_data_sim_0xmf = XDMFReader(registrationName=fpath.split('/')[-1], FileNames=[fpath])
|
||||
|
||||
# Limit the data array to be read
|
||||
# Properties modified on out_data_sim_0xmf
|
||||
out_data_sim_0xmf.PointArrayStatus = [name_dset]
|
||||
|
||||
# get active view
|
||||
renderView1 = GetActiveViewOrCreate('RenderView')
|
||||
|
||||
## show data in view
|
||||
#out_data_sim_0xmfDisplay = Show(out_data_sim_0xmf, renderView1, 'UnstructuredGridRepresentation')
|
||||
|
||||
## trace defaults for the display properties.
|
||||
#out_data_sim_0xmfDisplay.Representation = 'Surface'
|
||||
|
||||
# reset view to fit data
|
||||
#renderView1.ResetCamera(False)
|
||||
|
||||
# get the material library
|
||||
materialLibrary1 = GetMaterialLibrary()
|
||||
|
||||
# get color transfer function/color map for 'T_res_src_0_inv_0000'
|
||||
name_dsetLUT = GetColorTransferFunction(name_dset)
|
||||
|
||||
# get opacity transfer function/opacity map for 'T_res_src_0_inv_0000'
|
||||
name_dsetPWF = GetOpacityTransferFunction(name_dset)
|
||||
|
||||
|
||||
# show color bar/color legend
|
||||
#out_data_sim_0xmfDisplay.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# update the view to ensure updated data information
|
||||
#renderView1.Update()
|
||||
|
||||
# create a new 'Slice'
|
||||
slice1 = Slice(registrationName='Slice1', Input=out_data_sim_0xmf)
|
||||
|
||||
# Properties modified on slice1.SliceType
|
||||
slice1.SliceType.Normal = [0.0, 0.0, 1.0]
|
||||
|
||||
# show data in view
|
||||
slice1Display = Show(slice1, renderView1, 'GeometryRepresentation')
|
||||
|
||||
# trace defaults for the display properties.
|
||||
slice1Display.Representation = 'Surface'
|
||||
|
||||
# hide data in view
|
||||
Hide(out_data_sim_0xmf, renderView1)
|
||||
|
||||
# show color bar/color legend
|
||||
slice1Display.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# trace defaults for the display properties.
|
||||
slice1Display.Representation = 'Surface'
|
||||
|
||||
|
||||
# rescale color and/or opacity maps used to include current data range
|
||||
slice1Display.RescaleTransferFunctionToDataRange(True, False)
|
||||
|
||||
# show color bar/color legend
|
||||
slice1Display.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
|
||||
#
|
||||
# change the position of color bar
|
||||
#
|
||||
# Properties modified on slice1Display.DataAxesGrid
|
||||
slice1Display.DataAxesGrid.GridAxesVisibility = 1
|
||||
|
||||
# get color legend/bar for t_res_src_0_inv_0000LUT in view renderView1
|
||||
name_dsetLUTColorBar = GetScalarBar(name_dsetLUT, renderView1)
|
||||
|
||||
# change scalar bar placement
|
||||
name_dsetLUTColorBar.Orientation = 'Horizontal'
|
||||
name_dsetLUTColorBar.WindowLocation = 'Any Location'
|
||||
name_dsetLUTColorBar.Position = [0.33262344353799916, 0.24363636363636363]
|
||||
name_dsetLUTColorBar.ScalarBarLength = 0.3299999999999998
|
||||
|
||||
|
||||
|
||||
# update the view to ensure updated data information
|
||||
#renderView1.Update()
|
||||
|
||||
|
||||
#
|
||||
# axis options
|
||||
#
|
||||
|
||||
# toggle 3D widget visibility (only when running from the GUI)
|
||||
Hide3DWidgets(proxy=slice1.SliceType)
|
||||
|
||||
# Properties modified on slice1Display.DataAxesGrid
|
||||
slice1Display.DataAxesGrid.GridAxesVisibility = 1
|
||||
|
||||
|
||||
#
|
||||
# window layout and camera settings
|
||||
#
|
||||
layout1 = GetLayout()
|
||||
|
||||
#--------------------------------
|
||||
# saving layout sizes for layouts
|
||||
|
||||
# layout/tab size in pixels
|
||||
layout1.SetSize(1280, 980)
|
||||
|
||||
#-----------------------------------
|
||||
# saving camera placements for views
|
||||
|
||||
# current camera placement for renderView1
|
||||
renderView1.CameraPosition = [6086.06543558693, 0.0, 7825.811009542308]
|
||||
renderView1.CameraFocalPoint = [6086.06543558693, 0.0, -3.410605131648481e-13]
|
||||
renderView1.CameraViewUp = [1.0, 2.220446049250313e-16, 0.0]
|
||||
renderView1.CameraParallelScale = 2025.468932642534
|
||||
|
||||
# save screenshot
|
||||
SaveScreenshot('test_screenshot.png', renderView1, ImageResolution=[2560,1280])
|
||||
|
||||
Render()
|
||||
Interact()
|
||||
@@ -0,0 +1,115 @@
|
||||
# trace generated using paraview version 5.10.1
|
||||
#import paraview
|
||||
#paraview.compatibility.major = 5
|
||||
#paraview.compatibility.minor = 10
|
||||
|
||||
#### import the simple module from the paraview
|
||||
from paraview.simple import *
|
||||
#### disable automatic camera reset on 'Show'
|
||||
paraview.simple._DisableFirstRenderCameraReset()
|
||||
|
||||
# create a new 'XDMF Reader'
|
||||
out_data_sim_0xmf = XDMFReader(registrationName='out_data_sim_0.xmf', FileNames=['/home/masarunagaso/workspace/TomoATT/test/solver_performance/OUTPUT_FILES/out_data_sim_0.xmf'])
|
||||
|
||||
# get active view
|
||||
renderView1 = GetActiveViewOrCreate('RenderView')
|
||||
|
||||
# show data in view
|
||||
out_data_sim_0xmfDisplay = Show(out_data_sim_0xmf, renderView1, 'UnstructuredGridRepresentation')
|
||||
|
||||
# trace defaults for the display properties.
|
||||
out_data_sim_0xmfDisplay.Representation = 'Surface'
|
||||
|
||||
# reset view to fit data
|
||||
renderView1.ResetCamera(False)
|
||||
|
||||
# get the material library
|
||||
materialLibrary1 = GetMaterialLibrary()
|
||||
|
||||
# show color bar/color legend
|
||||
out_data_sim_0xmfDisplay.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# update the view to ensure updated data information
|
||||
renderView1.Update()
|
||||
|
||||
# get color transfer function/color map for 'procid'
|
||||
procidLUT = GetColorTransferFunction('procid')
|
||||
|
||||
# get opacity transfer function/opacity map for 'procid'
|
||||
procidPWF = GetOpacityTransferFunction('procid')
|
||||
|
||||
# create a new 'Slice'
|
||||
slice1 = Slice(registrationName='Slice1', Input=out_data_sim_0xmf)
|
||||
|
||||
# show data in view
|
||||
slice1Display = Show(slice1, renderView1, 'GeometryRepresentation')
|
||||
|
||||
# trace defaults for the display properties.
|
||||
slice1Display.Representation = 'Surface'
|
||||
|
||||
# hide data in view
|
||||
Hide(out_data_sim_0xmf, renderView1)
|
||||
|
||||
# show color bar/color legend
|
||||
slice1Display.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# update the view to ensure updated data information
|
||||
renderView1.Update()
|
||||
|
||||
# Properties modified on slice1.SliceType
|
||||
slice1.SliceType.Normal = [0.0, 0.0, 1.0]
|
||||
|
||||
# update the view to ensure updated data information
|
||||
renderView1.Update()
|
||||
|
||||
# set scalar coloring
|
||||
ColorBy(slice1Display, ('POINTS', 'T_res_src_0_inv_0000'))
|
||||
|
||||
# Hide the scalar bar for this color map if no visible data is colored by it.
|
||||
HideScalarBarIfNotNeeded(procidLUT, renderView1)
|
||||
|
||||
# rescale color and/or opacity maps used to include current data range
|
||||
slice1Display.RescaleTransferFunctionToDataRange(True, False)
|
||||
|
||||
# show color bar/color legend
|
||||
slice1Display.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# get color transfer function/color map for 'T_res_src_0_inv_0000'
|
||||
t_res_src_0_inv_0000LUT = GetColorTransferFunction('T_res_src_0_inv_0000')
|
||||
|
||||
# get opacity transfer function/opacity map for 'T_res_src_0_inv_0000'
|
||||
t_res_src_0_inv_0000PWF = GetOpacityTransferFunction('T_res_src_0_inv_0000')
|
||||
|
||||
# toggle 3D widget visibility (only when running from the GUI)
|
||||
Hide3DWidgets(proxy=slice1.SliceType)
|
||||
|
||||
# Properties modified on slice1Display.DataAxesGrid
|
||||
slice1Display.DataAxesGrid.GridAxesVisibility = 1
|
||||
|
||||
#================================================================
|
||||
# addendum: following script captures some of the application
|
||||
# state to faithfully reproduce the visualization during playback
|
||||
#================================================================
|
||||
|
||||
# get layout
|
||||
layout1 = GetLayout()
|
||||
|
||||
#--------------------------------
|
||||
# saving layout sizes for layouts
|
||||
|
||||
# layout/tab size in pixels
|
||||
layout1.SetSize(2329, 1650)
|
||||
|
||||
#-----------------------------------
|
||||
# saving camera placements for views
|
||||
|
||||
# current camera placement for renderView1
|
||||
renderView1.CameraPosition = [6086.06543558693, 0.0, 7825.811009542308]
|
||||
renderView1.CameraFocalPoint = [6086.06543558693, 0.0, -3.410605131648481e-13]
|
||||
renderView1.CameraViewUp = [1.0, 2.220446049250313e-16, 0.0]
|
||||
renderView1.CameraParallelScale = 2025.468932642534
|
||||
|
||||
#--------------------------------------------
|
||||
# uncomment the following to render all views
|
||||
# RenderAllViews()
|
||||
# alternatively, if you want to write images, you can use SaveScreenshot(...).
|
||||
@@ -0,0 +1,106 @@
|
||||
# trace generated using paraview version 5.10.1
|
||||
#import paraview
|
||||
#paraview.compatibility.major = 5
|
||||
#paraview.compatibility.minor = 10
|
||||
|
||||
#### import the simple module from the paraview
|
||||
from paraview.simple import *
|
||||
#### disable automatic camera reset on 'Show'
|
||||
paraview.simple._DisableFirstRenderCameraReset()
|
||||
|
||||
# create a new 'XDMF Reader'
|
||||
out_data_sim_0xmf = XDMFReader(registrationName='out_data_sim_0.xmf', FileNames=['/home/masarunagaso/workspace/TomoATT/test/solver_performance/OUTPUT_FILES/out_data_sim_0.xmf'])
|
||||
|
||||
# Properties modified on out_data_sim_0xmf
|
||||
out_data_sim_0xmf.PointArrayStatus = ['T_res_src_0_inv_0000']
|
||||
|
||||
# get active view
|
||||
renderView1 = GetActiveViewOrCreate('RenderView')
|
||||
|
||||
# show data in view
|
||||
out_data_sim_0xmfDisplay = Show(out_data_sim_0xmf, renderView1, 'UnstructuredGridRepresentation')
|
||||
|
||||
# trace defaults for the display properties.
|
||||
out_data_sim_0xmfDisplay.Representation = 'Surface'
|
||||
|
||||
# reset view to fit data
|
||||
renderView1.ResetCamera(False)
|
||||
|
||||
# get the material library
|
||||
materialLibrary1 = GetMaterialLibrary()
|
||||
|
||||
# show color bar/color legend
|
||||
out_data_sim_0xmfDisplay.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# update the view to ensure updated data information
|
||||
renderView1.Update()
|
||||
|
||||
# get color transfer function/color map for 'T_res_src_0_inv_0000'
|
||||
t_res_src_0_inv_0000LUT = GetColorTransferFunction('T_res_src_0_inv_0000')
|
||||
|
||||
# get opacity transfer function/opacity map for 'T_res_src_0_inv_0000'
|
||||
t_res_src_0_inv_0000PWF = GetOpacityTransferFunction('T_res_src_0_inv_0000')
|
||||
|
||||
# create a new 'Slice'
|
||||
slice1 = Slice(registrationName='Slice1', Input=out_data_sim_0xmf)
|
||||
|
||||
# Properties modified on slice1.SliceType
|
||||
slice1.SliceType.Normal = [0.0, 0.0, 1.0]
|
||||
|
||||
# show data in view
|
||||
slice1Display = Show(slice1, renderView1, 'GeometryRepresentation')
|
||||
|
||||
# trace defaults for the display properties.
|
||||
slice1Display.Representation = 'Surface'
|
||||
|
||||
# hide data in view
|
||||
Hide(out_data_sim_0xmf, renderView1)
|
||||
|
||||
# show color bar/color legend
|
||||
slice1Display.SetScalarBarVisibility(renderView1, True)
|
||||
|
||||
# update the view to ensure updated data information
|
||||
renderView1.Update()
|
||||
|
||||
# toggle 3D widget visibility (only when running from the GUI)
|
||||
Hide3DWidgets(proxy=slice1.SliceType)
|
||||
|
||||
# Properties modified on slice1Display.DataAxesGrid
|
||||
slice1Display.DataAxesGrid.GridAxesVisibility = 1
|
||||
|
||||
# get color legend/bar for t_res_src_0_inv_0000LUT in view renderView1
|
||||
t_res_src_0_inv_0000LUTColorBar = GetScalarBar(t_res_src_0_inv_0000LUT, renderView1)
|
||||
|
||||
# change scalar bar placement
|
||||
t_res_src_0_inv_0000LUTColorBar.Orientation = 'Horizontal'
|
||||
t_res_src_0_inv_0000LUTColorBar.WindowLocation = 'Any Location'
|
||||
t_res_src_0_inv_0000LUTColorBar.Position = [0.33262344353799916, 0.34363636363636363]
|
||||
t_res_src_0_inv_0000LUTColorBar.ScalarBarLength = 0.3299999999999998
|
||||
|
||||
#================================================================
|
||||
# addendum: following script captures some of the application
|
||||
# state to faithfully reproduce the visualization during playback
|
||||
#================================================================
|
||||
|
||||
# get layout
|
||||
layout1 = GetLayout()
|
||||
|
||||
#--------------------------------
|
||||
# saving layout sizes for layouts
|
||||
|
||||
# layout/tab size in pixels
|
||||
layout1.SetSize(2329, 1650)
|
||||
|
||||
#-----------------------------------
|
||||
# saving camera placements for views
|
||||
|
||||
# current camera placement for renderView1
|
||||
renderView1.CameraPosition = [6086.06543558693, 0.0, 7825.811009542308]
|
||||
renderView1.CameraFocalPoint = [6086.06543558693, 0.0, -3.410605131648481e-13]
|
||||
renderView1.CameraViewUp = [1.0, 2.220446049250313e-16, 0.0]
|
||||
renderView1.CameraParallelScale = 2025.468932642534
|
||||
|
||||
#--------------------------------------------
|
||||
# uncomment the following to render all views
|
||||
# RenderAllViews()
|
||||
# alternatively, if you want to write images, you can use SaveScreenshot(...).
|
||||
420
test/old_tests/solver_performance/run_performance_test.ipynb
Normal file
420
test/old_tests/solver_performance/run_performance_test.ipynb
Normal file
File diff suppressed because one or more lines are too long
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Reference in New Issue
Block a user