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136
test/old_tests/inversion_tele/1d_ak135.txt Normal file
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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
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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
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3392.310, 8.8036
3442.640, 8.8761
3492.970, 8.9461
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3794.960, 9.3205
3845.290, 9.3760
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4449.260, 9.9051
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4600.260, 10.0103
4650.590, 10.0439
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5053.240, 10.2745
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5711.740, 11.1941
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6218.860, 11.2586
6269.570, 11.2606
6320.290, 11.2618
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158
test/old_tests/inversion_tele/1d_model.txt Normal file
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5463, 11.3059
5473, 11.2888
5483, 11.2717
5493, 11.2546
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5513, 11.2203
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5533, 11.1853
5543, 11.1677
5553, 11.1502
5563, 11.1329
5573, 11.1168
5583, 11.1008
5593, 11.0847
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6043, 8.7307
6053, 8.6942
6063, 8.6577
6073, 8.6212
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6213, 8.15556
6223, 8.12778
6233, 8.1
6243, 8.07222
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6353, 5.8
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test/old_tests/inversion_tele/README.md Normal file
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# 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`

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test/old_tests/inversion_tele/check_1d_model_and_Tfield.ipynb Normal file
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{
"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
}

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200
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2.726 0.000 123.738
2.228 0.000 123.016

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30
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92.574 0.000 73.692 270.000 46.308

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40
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@@ -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

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test/old_tests/inversion_tele/input_params.yml Normal file
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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

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test/old_tests/inversion_tele/input_params_pre.yml Normal file
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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

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test/old_tests/inversion_tele/make_test_model.ipynb Normal file
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{
"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": []
}
],
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