# %% [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)