320 lines
10 KiB
Plaintext
320 lines
10 KiB
Plaintext
{
|
||
"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
|
||
}
|