First commit after changed file framework
这个提交包含在：
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import os
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from multiprocessing import Pool
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from functools import partial
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from time import time
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from shutil import rmtree
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import numpy as np
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from scipy.interpolate import interp1d
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from copy import deepcopy
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from pyat import ramRW_new as ramRW
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from pyat.DataBase import DataBase,soundSpeed
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class BathyM:
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def __init__(self, ran=None, depth=None):
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self.r = ran
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self.d = depth
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class SSP_:
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def __init__(self, r, z, c):
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self.r = r
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self.z = z
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self.c = c
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class Sed:
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def __init__(self, z, cp, cs, rho, a_p, a_s):
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self.z = z
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self.cp = cp
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self.cs = cs
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self.rho = rho
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self.a_p = a_p
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self.a_s = a_s
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class Coord:
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def __init__(self, lon, lat):
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self.lon = lon
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self.lat = lat
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class RANDI_Para:
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def __init__(self, baseDir, freq, lon, lat, Range, dRange, dTheta, v_ship, l_ship, theta=0):
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self.baseDir = baseDir
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self.freq = freq
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self.lon = lon
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self.lat = lat
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self.Range = Range
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self.dRange = dRange
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self.dTheta = dTheta
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self.v_ship = v_ship
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self.l_ship = l_ship
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self.theta = theta
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def refreshTheta(self, theta):
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self.theta = theta
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return self
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def RANDI_GetSeaDepth(data, N, coordS, R, azi):
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r = np.linspace(0, R, N)
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lon = coordS.lon + r * np.sin(azi) / (111 * np.cos(coordS.lat / 180 * np.pi))
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lat = coordS.lat + r * np.cos(azi) / 111
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z = np.zeros(N)
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for it in range(N):
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data.set_coord(lat[it], lon[it])
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z[it] = data.get_bottomDepth()
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return r, z
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def RANDI_GetMeanProfile(data, N, coordS, R, azi):
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r = np.linspace(0, R, N)
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lon = coordS.lon + r * np.sin(azi) / (111 * np.cos(coordS.lat / 180 * np.pi))
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lat = coordS.lat + r * np.cos(azi) / 111
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sal = np.full([len(data.depthGrid), N], np.nan)
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tem = np.full([len(data.depthGrid), N], np.nan)
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for i in range(N):
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data.set_coord(lat[i], lon[i])
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salPf = data.get_salRawProfile()
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temPf = data.get_temRawProfile()
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if len(salPf.x) > 1:
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sal[0:len(salPf.x), i] = salPf.y
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tem[0:len(temPf.x), i] = temPf.y
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sal = np.ma.masked_array(sal, np.isnan(sal))
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tem = np.ma.masked_array(tem, np.isnan(tem))
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sal_m = np.mean(sal, 1)
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tem_m = np.mean(tem, 1)
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z = data.depthGrid[~sal_m.mask]
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sal_m = sal_m[~sal_m.mask]
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tem_m = tem_m[~tem_m.mask]
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return z, sal_m, tem_m
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def RANDI_GetEnv(data, coordS, coordR=None, R=None, azi=None):
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if coordR == None:
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azi = azi / 180 * np.pi
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lon = coordS.lon + R * np.sin(azi) / (111 * np.cos(coordS.lat / 180 * np.pi))
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lat = coordS.lat + R * np.cos(azi) / 111
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coordR = Coord(lon, lat)
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if R == None:
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x = (coordR.lon - coordS.lon) * (111 * np.cos(coordS.lat / 180 * np.pi))
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y = (coordR.lat - coordS.lat) * 111
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R = np.sqrt(x * x + y * y)
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if y > 0:
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azi = np.arctan(x / y)
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elif y == 0:
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azi = np.sign(x) * np.pi / 2
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else:
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azi = np.arctan(x / y) + np.pi
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# Get Bathymetry
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N = int(np.ceil(R / 10) + 1)
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r, z = RANDI_GetSeaDepth(data, N, coordS, R, azi)
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bathym = BathyM(r, z)
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# plt.plot(r, z)
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# plt.gca().invert_yaxis()
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# plt.show()
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# Get Sound Speed Profile
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z_ssp, sal_m, tem_m = RANDI_GetMeanProfile(data, N, coordS, R, azi)
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if max(bathym.d) > z_ssp[-1]:
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z_ssp = np.append(z_ssp, max(bathym.d))
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sal_m = np.append(sal_m, sal_m[-1])
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tem_m = np.append(tem_m, tem_m[-1])
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c_ssp = soundSpeed(tem_m, sal_m, z_ssp)
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ssp = SSP_(0, z_ssp, c_ssp)
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# plt.plot(c_ssp, z_ssp)
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# plt.gca().invert_yaxis()
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# plt.show()
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# Sediment
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z = np.array([0, 50])
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cp = np.array([1550, 1590])
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cs = np.array([0, 0])
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rho = np.array([1.3, 1.5])
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a_p = np.array([0.1, 0.1])
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a_s = np.array([0, 0])
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sed = Sed(z, cp, cs, rho, a_p, a_s)
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return bathym, ssp, sed
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def RANDI_writeRAMin(baseDir, data, freq, dTheta, lat, lon, Range, rd, ship_sd, SeaDepthLim):
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t1 = time()
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btyFile = open("bty", 'w')
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for theta in np.arange(0, 360, dTheta):
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[bathm, ssp, sed] = RANDI_GetEnv(data, Coord(lon, lat), R=Range, azi=theta)
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for dd in bathm.d:
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btyFile.write(str(dd) + ' ')
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btyFile.write('\n')
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idx = np.where(bathm.d < SeaDepthLim)
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if len(idx[0]) > 0:
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bathm.r = bathm.r[0:idx[0][0]]
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bathm.d = bathm.d[0:idx[0][0]]
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title = "Waveguide"
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# Source and receiving position
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bathm.r = bathm.r * 1000 # km -> m
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rmax = max(bathm.r) # Maximum receiving range (unit: m)
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zmax = round(max(bathm.d) + 5 * 1500 / freq) # Maximum receiving depth (uint: m)
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zmplt = 0 # round(max(bathm.d)*1.05) # Maximum depth of plot (uint: m)
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dz = 1500 / freq / 4 # Step in depth direction: wavelength / 15
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dr = 5 * dz # Step in range direction
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pos = ramRW.PosRAM(rd, ship_sd, rmax, zmax, dr, dz, zmplt)
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# Sound speed profile for RAM
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Z = sed.z
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cw_p = ramRW.PROF(ssp.z, ssp.c) # Water sound speed profile
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cb_p = ramRW.PROF(Z, sed.cp) # Bottom sound speed profile
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rhob_p = ramRW.PROF(Z, sed.rho) # Sea bottom density profile
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Ap = sed.a_p
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if Z[-1] < 5 * 1500 / freq:
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Z = np.append(Z, 3 * 1500 / freq)
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Ap = np.append(Ap, Ap[-1])
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Z = np.append(Z, Z[-1] + 2 * 1500 / freq)
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Ap = np.append(Ap, 10)
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# Ap = sed[it].a_p
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attn_p = ramRW.PROF(Z, Ap) # Sea bottom attenuation profile
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ssp_ram = [ramRW.SSPRAM(0, cw_p, cb_p, rhob_p, attn_p)]
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# Write ram.in file
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if not os.path.exists(baseDir + "/TL/temp/theta_{:1d}".format(theta)):
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os.makedirs(baseDir + "/TL/temp/theta_{:1d}".format(theta))
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envfil = baseDir + "/TL/temp/theta_{:1d}/ram.in".format(theta)
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ramRW.write_env_RAM(title, envfil, freq, pos, bathm, ssp_ram)
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t2 = time()
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#print(t2 - t1)
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btyFile.close()
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def RANDI_callRAM(baseDir, NThreads, freq, dTheta):
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'''
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t1 = time()
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for theta in np.arange(0,360,5):
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os.chdir(baseDir + "/TL/theta_{:1d}".format(theta))
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os.system(baseDir + "/ram.exe")
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os.chdir(baseDir)
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t2 = time()
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print(t2-t1)
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'''
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t1 = time()
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func = partial(callRAM, baseDir)
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pool = Pool(NThreads)
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pool.map(func, np.arange(0, 360, dTheta))
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t2 = time()
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#print(t2 - t1)
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if os.path.exists(baseDir + f"/TL/freq_{round(freq)}"):
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rmtree(baseDir + f"/TL/freq_{round(freq)}")
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os.rename(baseDir + "/TL/temp", baseDir + f"/TL/freq_{round(freq)}")
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def callRAM(baseDir, theta):
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AtBinPath = os.path.dirname(os.path.abspath(__file__))+'/at/bin'
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print(AtBinPath)
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os.chdir(baseDir + "/TL/temp/theta_{:1d}".format(theta))
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os.system(AtBinPath + "/ram")
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os.chdir(baseDir)
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def RANDI_getShipNum(lat, lon, Range, dRange, theta):
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NRange = int(Range / dRange)
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#shipNum = np.random.rand(NRange)
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shipNum = 0.5*np.ones(NRange)
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return shipNum
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def calNoise(randiP):
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rr = np.arange(randiP.dRange / 2, randiP.Range, randiP.dRange)
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SL = RossShipSL(randiP.freq, randiP.v_ship, randiP.l_ship)
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S = np.power(10, SL / 10)
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shipNum = RANDI_getShipNum(randiP.lat, randiP.lon, randiP.Range, randiP.dRange, randiP.theta)
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filePath = randiP.baseDir + f"/TL/freq_{round(randiP.freq)}/theta_{round(randiP.theta)}"
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[r, tl] = ramRW.readTLline_RAM(filePath)
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r = r / 1000
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I2 = np.power(10, tl / 10)
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I_ = interp1d(r, I2)
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I = I_(rr[rr < r[-1]])
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noise = sum(shipNum[rr < r[-1]] * S / I)
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return noise
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def RANDI_calNL(randiP, NThreads):
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'''
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t1 = time()
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theta = np.arange(0, 360, dTheta)
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noise1 = np.zeros(len(theta))
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for i in range(len(theta)):
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randiP.theta = theta[i]
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noise1[i] = calNoise(randiP)
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NL1 = 10 * np.log10(sum(noise1))
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t2 = time()
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print(t2-t1)
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'''
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t1 = time()
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RANDI_P = []
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for theta in np.arange(0, 360, randiP.dTheta):
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randiP.theta = theta
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RANDI_P.append(deepcopy(randiP))
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pool = Pool(NThreads)
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noise = pool.map(calNoise, RANDI_P)
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NL = 10 * np.log10(sum(noise))
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t2 = time()
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#print(t2-t1)
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return NL
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def RossShipSL(freq, v, l):
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if freq < 500:
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Lso = -10 * np.log10(np.power(10, -1.06 * np.log10(freq) - 14.34) +
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np.power(10, 3.32 * np.log10(freq) - 21.425))
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else:
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Lso = 173.2 - 18 * np.log10(freq)
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if freq <= 28.4:
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df = 8.1
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elif freq < 191.6:
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df = 22.3-9.77*np.log10(freq)
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else:
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df = 0
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dl = np.power(l, 1.15) / 3643
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Ls = Lso + 60*np.log10(v/12) + 20*np.log10(l/300) + df*dl + 3
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return Ls
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def call_RANDI(ETOPO1Path, STPath, baseDir, freq, rd, lon, lat, timeType, NThreads):
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# 定义时间段
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timeIndex = timeType
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# 创建类
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data = DataBase(ETOPO1Path, STPath)
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# 设置时间段
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data.set_timePeriod(timeIndex)
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Range = 500 # Range of sound field calculation (Unit: km)
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ship_sd = 6.0 # Ship source depth (Unit: m)
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dTheta = 5 # The angle of sector (Unit: °)
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dRange = 10 # The
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SeaDepthLim = 20 # (Unut: m)
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v_ship = 12 # Ship speed (Unit: kt)
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l_ship = 300 # Ship length (Unit: ft)
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randiP = RANDI_Para(baseDir, freq, lon, lat, Range, dRange, dTheta, v_ship, l_ship)
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RANDI_writeRAMin(baseDir, data, freq, dTheta, lat, lon, Range, rd, ship_sd, SeaDepthLim)
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RANDI_callRAM(baseDir, NThreads, freq, dTheta)
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NL = RANDI_calNL(randiP, NThreads)
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return NL
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