241 lines
6.7 KiB
Python
241 lines
6.7 KiB
Python
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# %% [markdown]
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# # notebook for create init and true test model
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# %%
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import numpy as np
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import math
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# grid
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R_earth = 6371.0
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rr1=6361
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rr2=6381
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tt1=(38.0-0.3)/180*math.pi
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tt2=(42.0+0.3)/180*math.pi
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pp1=(23.0-0.3)/180*math.pi
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pp2=(27.0+0.3)/180*math.pi
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n_rtp = [10,50,50]
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dr = (rr2-rr1)/(n_rtp[0]-1)
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dt = (tt2-tt1)/(n_rtp[1]-1)
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dp = (pp2-pp1)/(n_rtp[2]-1)
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rr = np.array([rr1 + x*dr for x in range(n_rtp[0])])
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tt = np.array([tt1 + x*dt for x in range(n_rtp[1])])
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pp = np.array([pp1 + x*dp for x in range(n_rtp[2])])
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# initial model
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gamma = 0.0
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s0 = 1.0/6.0
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slow_p=0.06
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ani_p=0.04
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eta_init = np.zeros(n_rtp)
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xi_init = np.zeros(n_rtp)
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zeta_init = np.zeros(n_rtp)
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fun_init = np.zeros(n_rtp)
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vel_init = np.zeros(n_rtp)
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# true model
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eta_true = np.zeros(n_rtp)
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xi_true = np.zeros(n_rtp)
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zeta_true = np.zeros(n_rtp)
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fun_true = np.zeros(n_rtp)
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vel_true = np.zeros(n_rtp)
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c=0
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for ir in range(n_rtp[0]):
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for it in range(n_rtp[1]):
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for ip in range(n_rtp[2]):
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# already initialized above
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#eta_init[ir,it,ip] = 0.0
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#xi_init[ir,it,ip] = 0.0
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zeta_init[ir,it,ip] = gamma*math.sqrt(eta_init[ir,it,ip]**2 + xi_init[ir,it,ip]**2)
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fun_init[ir,it,ip] = s0
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vel_init[ir,it,ip] = 1.0/s0
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# true model
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if (tt[it] >= 38.0/180.0*math.pi and tt[it] <= 42.0/180.0*math.pi \
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and pp[ip] >= 23.0/180.0*math.pi and pp[ip] <= 27.0/180.0*math.pi):
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c+=1
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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))
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else:
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sigma = 0.0
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if sigma < 0:
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psi = 60.0/180.0*math.pi
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elif sigma > 0:
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psi = 120.0/180.0*math.pi
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else:
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psi = 0.0
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eta_true[ir,it,ip] = ani_p*abs(sigma)*math.sin(2.0*psi)
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xi_true[ir,it,ip] = ani_p*abs(sigma)*math.cos(2.0*psi)
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zeta_true[ir,it,ip] = gamma*math.sqrt(eta_true[ir,it,ip]**2 + xi_true[ir,it,ip]**2)
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fun_true[ir,it,ip] = s0/(1.0+sigma*slow_p)
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vel_true[ir,it,ip] = 1.0/fun_true[ir,it,ip]
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#r_earth = 6378.1370
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print("depminmax {} {}".format(R_earth-rr1,R_earth-rr2))
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print(c)
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# %%
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# write out in hdf5 format
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import h5py
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fout_init = h5py.File('test_model_init.h5', 'w')
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fout_true = h5py.File('test_model_true.h5', 'w')
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# write out the arrays eta_init, xi_init, zeta_init, fun_init, a_init, b_init, c_init, f_init
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fout_init.create_dataset('eta', data=eta_init)
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fout_init.create_dataset('xi', data=xi_init)
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fout_init.create_dataset('zeta', data=zeta_init)
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fout_init.create_dataset('vel', data=vel_init)
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# writeout the arrays eta_true, xi_true, zeta_true, fun_true, a_true, b_true, c_true, f_true
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fout_true.create_dataset('eta', data=eta_true)
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fout_true.create_dataset('xi', data=xi_true)
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fout_true.create_dataset('zeta', data=zeta_true)
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fout_true.create_dataset('vel', data=vel_true)
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fout_init.close()
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fout_true.close()
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# %% [markdown]
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# # prepare src station file
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#
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# The following code creates a src_rec_file for the inversion, which describes the source and receiver positions and arrival times.
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# Format is as follows:
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#
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# ```
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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
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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
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# 26 2 MRPI 1.6125 99.3172 1100.0000 P 50.84 19.400
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# 26 3 HUTI 2.3153 98.9711 1600.0000 P 57.84 19.200
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# ....
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#
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# ```
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# %%
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import random
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random.seed(1145141919810)
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# dummys
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year_dummy = 1998
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month_dummy = 1
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day_dummy = 1
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hour_dummy = 0
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minute_dummy = 0
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second_dummy = 0
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mag_dummy = 3.0
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id_dummy = 1000
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st_name_dummy = 'AAAA'
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phase_dummy = 'P'
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arriv_t_dummy = 0.0
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weight_dummy = 0.444
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tt1deg = tt1 * 180.0/math.pi
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tt2deg = tt2 * 180.0/math.pi
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pp1deg = pp1 * 180.0/math.pi
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pp2deg = pp2 * 180.0/math.pi
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n_srcs = [10,20,20]
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#n_srcs = [2,1,1]
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n_src = n_srcs[0]*n_srcs[1]*n_srcs[2]
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n_rec = [30 for x in range(n_src)]
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lines = []
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nij_rec = math.sqrt(n_rec[0])
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pos_src=[]
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pos_rec=[]
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# create receiver coordinates
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elev_recs=[]
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lon_recs=[]
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lat_recs=[]
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rec_names=[]
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for i in range(n_rec[0]):
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#elev_recs.append(random.uniform(-100.0,-100.0)) # elevation in m
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#elev_recs.append(0) # elevation in m
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#lon_recs .append(random.uniform(pp1deg*1.1,pp2deg*0.9))
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#lat_recs .append(random.uniform(tt1deg*1.1,tt2deg*0.9))
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rec_names.append(i)
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# regularly
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elev_recs.append(0.0)
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tmp_ilon = i%nij_rec
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tmp_ilat = int(i/nij_rec)
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lon_recs.append(pp1deg + tmp_ilon*(pp2deg-pp1deg)/nij_rec)
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lat_recs.append(tt1deg + tmp_ilat*(tt2deg-tt1deg)/nij_rec)
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# create source coordinates
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for ir in range(n_srcs[0]):
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for it in range(n_srcs[1]):
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for ip in range(n_srcs[2]):
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i_src = ir*n_srcs[1]*n_srcs[2] + it*n_srcs[2] + ip
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# define one point in the domain (rr1 bottom, rr2 top)
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# random
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#dep = random.uniform((R_earth-rr1)*0.5,(R_earth-rr1)*0.98)
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#lon = random.uniform(pp1deg,pp2deg)
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#lat = random.uniform(tt1deg,tt2deg)
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# regular
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dep = (R_earth-rr1)/n_srcs[0]*ir
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lon = pp1deg + ip*(pp2deg-pp1deg)/n_srcs[2]
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lat = tt1deg + it*(tt2deg-tt1deg)/n_srcs[1]
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# put independent name for each source
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id_dummy = "src_"+str(i_src)
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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, weight_dummy]
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lines.append(src)
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pos_src.append([lon,lat,dep])
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# create dummy station
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for i_rec in range(n_rec[i_src]):
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elev_rec = elev_recs[i_rec]
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lon_rec = lon_recs[i_rec]
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lat_rec = lat_recs[i_rec]
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st_name_dummy = "rec_"+str(rec_names[i_rec])
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rec = [i_src, i_rec, st_name_dummy, lat_rec, lon_rec, elev_rec, phase_dummy, arriv_t_dummy, weight_dummy]
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lines.append(rec)
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pos_rec.append([lon_rec,lat_rec,elev_rec])
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# write out ev_arrivals file
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fname = 'src_rec_test.dat'
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with open(fname, 'w') as f:
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for line in lines:
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for elem in line:
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f.write('{} '.format(elem))
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f.write('\n')
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# # %%
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# # draw src and rec positions
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# import matplotlib.pyplot as plt
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# for i_src in range(n_src):
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# plt.scatter(pos_src[i_src][1],pos_src[i_src][0],c='r',marker='o')
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# # %%
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# # plot receivers
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# for i_rec in range(n_rec[0]):
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# plt.scatter(pos_rec[i_rec][1],pos_rec[i_rec][0],c='b',marker='o')
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