339 lines
11 KiB
Plaintext
339 lines
11 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# notebook for create init and true test model"
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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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"import numpy as np\n",
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"import math\n",
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"\n",
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"# grid\n",
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"#R_earth = 6378.1370\n",
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"R_earth = 6371.0\n",
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"\n",
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"rr1=6361 \n",
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"rr2=6381\n",
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"tt1=(38.0-0.3)/180*math.pi\n",
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"tt2=(42.0+0.3)/180*math.pi\n",
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"pp1=(23.0-0.3)/180*math.pi\n",
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"pp2=(27.0+0.3)/180*math.pi\n",
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"\n",
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"n_rtp = [10,50,50]\n",
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"n_rtp.reverse()\n",
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"dr = (rr2-rr1)/(n_rtp[2]-1)\n",
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"dt = (tt2-tt1)/(n_rtp[1]-1)\n",
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"dp = (pp2-pp1)/(n_rtp[0]-1)\n",
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"rr = np.array([rr1 + x*dr for x in range(n_rtp[2])])\n",
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"tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])\n",
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"pp = np.array([pp1 + x*dp for x in range(n_rtp[0])])\n",
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"\n",
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"# initial model\n",
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"gamma = 0.0\n",
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"s0 = 1.0/6.0\n",
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"slow_p=0.06\n",
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"ani_p=0.04\n",
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"\n",
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"eta_init = np.zeros(n_rtp)\n",
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"xi_init = np.zeros(n_rtp)\n",
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"zeta_init = np.zeros(n_rtp)\n",
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"fun_init = np.zeros(n_rtp)\n",
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"vel_init = np.zeros(n_rtp)\n",
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"a_init = np.zeros(n_rtp)\n",
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"b_init = np.zeros(n_rtp)\n",
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"c_init = np.zeros(n_rtp)\n",
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"f_init = np.zeros(n_rtp)\n",
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"\n",
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"# true model\n",
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"eta_true = np.zeros(n_rtp)\n",
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"xi_true = np.zeros(n_rtp)\n",
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"zeta_true = np.zeros(n_rtp)\n",
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"fun_true = np.zeros(n_rtp)\n",
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"vel_true = np.zeros(n_rtp)\n",
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"a_true = np.zeros(n_rtp)\n",
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"b_true = np.zeros(n_rtp)\n",
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"c_true = np.zeros(n_rtp)\n",
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"f_true = np.zeros(n_rtp)\n",
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"\n",
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"c=0\n",
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"for ir in range(n_rtp[2]):\n",
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" for it in range(n_rtp[1]):\n",
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" for ip in range(n_rtp[0]):\n",
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" #eta_init[ip,it,ir] = 0.0\n",
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" #xi_init[ip,it,ir] = 0.0\n",
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" zeta_init[ip,it,ir] = gamma*math.sqrt(eta_init[ip,it,ir]**2 + xi_init[ip,it,ir]**2)\n",
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" fun_init[ip,it,ir] = s0\n",
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" vel_init[ip,it,ir] = 1.0/s0\n",
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" a_init[ip,it,ir] = 1.0 + 2.0*zeta_init[ip,it,ir]\n",
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" b_init[ip,it,ir] = 1.0 - 2.0*xi_init[ip,it,ir]\n",
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" c_init[ip,it,ir] = 1.0 + 2.0*xi_init[ip,it,ir]\n",
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" f_init[ip,it,ir] = -2.0 * eta_init[ip,it,ir]\n",
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"\n",
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" # true model\n",
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" if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \\\n",
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" and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):\n",
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" c+=1\n",
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" 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",
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" else:\n",
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" sigma = 0.0\n",
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"\n",
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" if sigma < 0:\n",
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" psi = 60.0/180.0*math.pi\n",
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" elif sigma > 0:\n",
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" psi = 120.0/180.0*math.pi\n",
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" else:\n",
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" psi = 0.0\n",
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"\n",
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" eta_true[ip,it,ir] = ani_p*abs(sigma)*math.sin(2.0*psi)\n",
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" xi_true[ip,it,ir] = ani_p*abs(sigma)*math.cos(2.0*psi)\n",
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" zeta_true[ip,it,ir] = gamma*math.sqrt(eta_true[ip,it,ir]**2 + xi_true[ip,it,ir]**2)\n",
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" fun_true[ip,it,ir] = s0/(1.0+sigma*slow_p)\n",
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" vel_true[ip,it,ir] = 1.0/fun_true[ip,it,ir] \n",
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" a_true[ip,it,ir] = 1.0 + 2.0*zeta_true[ip,it,ir]\n",
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" b_true[ip,it,ir] = 1.0 - 2.0*xi_true[ip,it,ir]\n",
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" c_true[ip,it,ir] = 1.0 + 2.0*xi_true[ip,it,ir]\n",
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" f_true[ip,it,ir] = -2.0 * eta_true[ip,it,ir]\n",
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"\n",
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"\n",
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"\n",
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"#r_earth = 6378.1370\n",
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"print(\"depminmax {} {}\".format(R_earth-rr1,R_earth-rr2))\n",
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"print(c)\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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"# write out in ASCIII\n",
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"\n",
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"#\n",
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"\n",
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"fname_init = 'test_model_init.dat'\n",
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"fname_true = 'test_model_true.dat'\n",
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"\n",
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"\n",
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"# write init model\n",
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"with open(fname_init, 'w') as f:\n",
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" # write nodes in rtp\n",
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" for ir in range(n_rtp[2]):\n",
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" for it in range(n_rtp[1]):\n",
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" for ip in range(n_rtp[0]):\n",
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" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
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" 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",
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"\n",
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"\n",
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"# write true model\n",
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"with open(fname_true, 'w') as f:\n",
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" # write nodes in rtp\n",
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" for ir in range(n_rtp[2]):\n",
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" for it in range(n_rtp[1]):\n",
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" for ip in range(n_rtp[0]):\n",
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" # write out eta xi zeta fun fac_a fac_b fac_c fac_f\n",
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" 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",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# prepare src station file\n",
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"\n",
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"```\n",
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" 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",
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" 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",
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" 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400\n",
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" 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200\n",
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"\n",
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"```"
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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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"import random\n",
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"random.seed(1145141919810)\n",
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"\n",
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"# dummys\n",
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"year_dummy = 1998\n",
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"month_dummy = 1\n",
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"day_dummy = 1\n",
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"hour_dummy = 0\n",
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"minute_dummy = 0\n",
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"second_dummy = 0\n",
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"mag_dummy = 3.0\n",
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"id_dummy = 1000\n",
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"st_name_dummy = 'AAAA'\n",
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"phase_dummy = 'P'\n",
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"dist_dummy = 100.0\n",
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"arriv_t_dummy = 0.0\n",
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"\n",
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"tt1deg = tt1 * 180.0/math.pi\n",
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"tt2deg = tt2 * 180.0/math.pi\n",
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"pp1deg = pp1 * 180.0/math.pi\n",
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"pp2deg = pp2 * 180.0/math.pi\n",
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"\n",
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"\n",
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"n_src = 500\n",
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"n_rec = [30 for x in range(n_src)]\n",
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"\n",
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"\n",
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"lines = []\n",
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"\n",
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"nij_src = math.sqrt(n_src)\n",
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"nij_rec = math.sqrt(n_rec[0])\n",
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"\n",
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"pos_src=[]\n",
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"pos_rec=[]\n",
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"\n",
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"\n",
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"# create receiver coordinates\n",
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"elev_recs=[]\n",
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"lon_recs=[]\n",
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"lat_recs=[]\n",
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"rec_names=[]\n",
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"for i in range(n_rec[0]):\n",
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" #elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m\n",
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" #elev_recs.append(0) # elevation in m\n",
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" #lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))\n",
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" #lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))\n",
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" rec_names.append(i)\n",
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" # regularly\n",
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" elev_recs.append(0.0)\n",
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" tmp_ilon = i%nij_rec\n",
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" tmp_ilat = int(i/nij_rec)\n",
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" lon_recs.append(pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec)\n",
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" lat_recs.append(tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec)\n",
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"\n",
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"\n",
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"\n",
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"# create dummy src\n",
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"for i_src in range(n_src):\n",
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" # define one point in the domain (rr1 bottom, rr2 top)\n",
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" # random\n",
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" #dep = random.uniform((R_earth-rr1)*0.5,(R_earth-rr1)*0.98)\n",
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" #lon = random.uniform(pp1deg,pp2deg)\n",
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" #lat = random.uniform(tt1deg,tt2deg)\n",
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"\n",
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" # regularl\n",
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" dep = (R_earth-rr1)*0.9\n",
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" tmp_ilon = i_src%nij_src\n",
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" tmp_ilat = int(i_src/nij_src)\n",
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" lon = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_src\n",
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" lat = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_src\n",
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"\n",
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" 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",
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" lines.append(src)\n",
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"\n",
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" pos_src.append([lon,lat,dep])\n",
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"\n",
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"\n",
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" # create dummy station\n",
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" for i_rec in range(n_rec[i_src]):\n",
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" #elev_rec = 0.0 #random.uniform(0.0,-10.0) # elevation in m\n",
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" #lon_rec = random.uniform(pp1deg,pp2deg)\n",
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" #lat_rec = random.uniform(tt1deg,tt2deg)\n",
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" # regularly\n",
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" #elev_rec = -10.0\n",
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" #tmp_ilon = i_rec%nij_rec\n",
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" #tmp_ilat = int(i_rec/nij_rec)\n",
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" #lon_rec = pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec\n",
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" #lat_rec = tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec\n",
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"\n",
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" # \n",
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" elev_rec = elev_recs[i_rec]\n",
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" lon_rec = lon_recs[i_rec]\n",
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" lat_rec = lat_recs[i_rec]\n",
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" st_name_dummy = rec_names[i_rec]\n",
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"\n",
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" rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, dist_dummy, arriv_t_dummy]\n",
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" lines.append(rec)\n",
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"\n",
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" pos_rec.append([lon_rec,lat_rec,elev_rec])\n",
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"\n",
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"\n",
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"# write out ev_arrivals file\n",
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"fname = 'src_rec_test.dat'\n",
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"\n",
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"with open(fname, 'w') as f:\n",
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" for line in lines:\n",
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" for elem in line:\n",
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" f.write('{} '.format(elem))\n",
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" f.write('\\n')\n",
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" "
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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": {},
|
|||
|
|
"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
|
|||
|
|
}
|