# -*- coding: utf-8 -*- import warnings warnings.filterwarnings('ignore') import argparse, json from common import NoIndent, MyEncoder def _argparse(): parser = argparse.ArgumentParser(description='tl realtime client') parser.add_argument('-a', '--argfile', action='store', dest='argfile', required=True, help='name of arguments file') return parser.parse_args() def main(): parser = _argparse() argfile = parser.argfile if argfile[-5:] != '.json': print('输入的参数文件名有误') return with open(argfile,'r') as jsonFile: paramData = json.load(jsonFile) if ("freq" not in paramData) or ("sourceDepth" not in paramData) or\ ("receiveDepth" not in paramData) or ("modelType" not in paramData) or\ ("bathyfile" not in paramData) or ("sspfile" not in paramData) or\ ("z_min" not in paramData) or ("z_max" not in paramData) or\ ("cp_min" not in paramData) or ("cp_max" not in paramData) or\ ("cs_min" not in paramData) or ("cs_max" not in paramData) or\ ("rho_min" not in paramData) or ("rho_max" not in paramData) or\ ("ap_min" not in paramData) or ("ap_max" not in paramData) or\ ("as_min" not in paramData) or ("as_max" not in paramData) or\ ("Cb_p" not in paramData) or ("Cb_s" not in paramData) or\ ("Rhob" not in paramData) or ("Ab_p" not in paramData) or\ ("Ab_s" not in paramData) or ("png" not in paramData) or\ ("outParam" not in paramData): print(f'{argfile}中的参数有误，请核实！') return freq = float(paramData["freq"]) sourceDepth = float(paramData["sourceDepth"]) receiveDepth = float(paramData["receiveDepth"]) modelType = paramData["modelType"] btyfile = paramData["bathyfile"] sspfile = paramData["sspfile"] z_min = float(paramData["z_min"]) z_max = float(paramData["z_max"]) cp_min = float(paramData["cp_min"]) cp_max = float(paramData["cp_max"]) cs_min = float(paramData["cs_min"]) cs_max = float(paramData["cs_max"]) rho_min = float(paramData["rho_min"]) rho_max = float(paramData["rho_max"]) ap_min = float(paramData["ap_min"]) ap_max = float(paramData["ap_max"]) as_min = float(paramData["as_min"]) as_max = float(paramData["as_max"]) Cb_p = float(paramData["Cb_p"]) Cb_s = float(paramData["Cb_s"]) Rhob = float(paramData["Rhob"]) Ab_p = float(paramData["Ab_p"]) Ab_s = float(paramData["Ab_s"]) png = paramData["png"] outParam = paramData["outParam"] from scipy.interpolate import Akima1DInterpolator import numpy as np from pyat.AcousticPara import BathyM, Base, Sed, SSP_ from pyat.tlcore import call_Bellhop, call_krakenc, call_ram import matplotlib.pyplot as plt bathym, ssp, sed, base = [], [], [], [] with open(btyfile, 'r') as f: lines = f.readlines() if len(lines) < 1: print(f'{btyfile}中的参数有误，请核实！') return # 读取数据 data = np.loadtxt(btyfile, skiprows=1, usecols=(0, 1)) bathym = BathyM(data[:, 0], data[:, 1]) profile_num = 0 with open(sspfile, 'r') as f: try: line = f.readline() profile_num = int((line.split())[0]) while line: line = f.readline() if '距离' in line: ranges, depths, vels = [], [], [] line = f.readline() while line and ('分隔符' not in line): ranges.append(1) depths.append(float((line.split())[0])) vels.append(float((line.split())[1])) line = f.readline() ssp.append(SSP_(ranges, depths, vels)) except Exception as err: print(f'{sspfile}中的参数有误，请核实！') print(err) return """akima 0829""" z_ssp = np.array([]) for i in range(len(ssp)): z_ssp = np.append(z_ssp, ssp[i].z) z_ssp = np.unique(z_ssp) z_ssp = np.sort(z_ssp) for i in range(len(ssp)): dep = ssp[i].z vel = ssp[i].c # 对剖面进行垂向插值处理 depInterp = z_ssp[z_ssp<=ssp[i].z[-1]] # 应用Akima插值算法，对ssp进行插值 func = Akima1DInterpolator(dep, vel) velInterp = func(depInterp) # 剖面赋值 ssp[i].z = depInterp ssp[i].c = velInterp len_real = len(depInterp)-1 #for it in range(len_real,int(deep_max)): # ssp[i].c = np.append(ssp[i].c,0) # Sediment z = np.array([z_min, z_max]) cp = np.array([cp_min, cp_max]) cs = np.array([cs_min, cs_max]) rho = np.array([rho_min, rho_max]) a_p = np.array([ap_min, ap_max]) a_s = np.array([as_min, as_max]) for it in range(profile_num): sed.append(Sed(z, cp, cs, rho, a_p, a_s)) # Base base = [] for it in range(profile_num): base.append(Base(Cb_p, Cb_s, Rhob, Ab_p, Ab_s)) ranges, depths, TL = [], [], [] if modelType == 'bellhop': sd = np.array([sourceDepth]) # Source depth rd = np.linspace(0, receiveDepth, int(receiveDepth / 10)) # Receiving depth [Pos, TL] = call_Bellhop(freq, sd, rd, bathym, ssp, sed, base) ranges, depths, TL = Pos.r.range, Pos.r.depth, TL[0,0,:,:] # Plot if png: plt.pcolor(Pos.r.range, Pos.r.depth, TL[0, 0, :, :], vmin=40, vmax=130, cmap='jet_r', shading='auto') plt.xlabel("Range/m") plt.ylabel("Depth/m") plt.gca().invert_yaxis() plt.colorbar() plt.show() print(TL[0, 0, :, :]) elif modelType == 'kraken': sd = np.array([sourceDepth]) # Source depth rd = np.linspace(0, receiveDepth, int(receiveDepth / 10)) # Receiving depth [Pos, TL] = call_krakenc(freq, sd, rd, bathym, ssp, sed, base) ranges, depths, TL = Pos.r.range, Pos.r.depth, TL[0,0,:,:] # Plot if png: plt.pcolor(Pos.r.range, Pos.r.depth, TL[0, 0, :, :], vmin=40, vmax=130, cmap='jet_r', shading='auto') plt.xlabel("Range/m") plt.ylabel("Depth/m") plt.gca().invert_yaxis() plt.colorbar() plt.show() elif modelType == 'ram': # 调用ram模块 [rd, rr, TL] = call_ram(freq, sourceDepth, receiveDepth, bathym, ssp, sed) ranges, depths, TL = rr, rd, TL # Plot if png: plt.pcolormesh(rr, rd, TL, vmin=60, vmax=130, cmap='jet_r', shading='auto') plt.xlabel("Range/m") plt.ylabel("Depth/m") plt.gca().invert_yaxis() plt.colorbar() plt.show() # 保存地形数据 bathym.r = np.around(bathym.r, decimals=0) bathym.d = np.around(bathym.d, decimals=0) bathymData = { "param": paramData, "count": len(bathym.d), "descript": "距离、深度", "data": NoIndent(list(zip(bathym.r, bathym.d))) } with open(("" if outParam["outPath"]=="" else outParam["outPath"] + "/")+"tlRealtimeOut_bathym.json", 'w') as jsonFile: json_data = json.dumps(bathymData, cls=MyEncoder, indent=2, ensure_ascii=False) jsonFile.write(json_data) # 保存传播损失数据 tlpoint = [] depths = np.around(depths, decimals=0) ranges = np.around(ranges, decimals=0) TL = np.around(TL, decimals=2) tlpoint = list(zip(np.tile(depths.reshape(len(depths),1),len(ranges)).flatten(), np.tile(ranges,(len(depths),1)).flatten(), TL.flatten())) tlData = { "param": paramData, "count": len(ranges)*len(depths), "descript": "距离、深度、损失", "data": NoIndent(tlpoint) } with open(("" if outParam["outPath"]=="" else outParam["outPath"] + "/")+"tlRealtimeOut_tl.json", 'w') as jsonFile: json_data = json.dumps(tlData, cls=MyEncoder, indent=2, ensure_ascii=False) jsonFile.write(json_data) if __name__ == '__main__': main()