60 行
2.1 KiB
Python
60 行
2.1 KiB
Python
# -*- coding: utf-8 -*-
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import warnings
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warnings.filterwarnings('ignore')
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import argparse, json
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def _argparse():
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parser = argparse.ArgumentParser(description='Wind Generated Noise Prediction')
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parser.add_argument('-a', '--argfile', action='store', dest='argfile', required=True, help='name of arguments file')
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return parser.parse_args()
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def main():
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parser = _argparse()
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argfile = parser.argfile
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if argfile[-5:] != '.json':
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print('输入的参数文件名有误')
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return
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with open(argfile,'r') as jsonFile:
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paramData = json.load(jsonFile)
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if ("dataFile" not in paramData) or ("freq" not in paramData) or\
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("depth" not in paramData) or ("windSpeed" not in paramData) or\
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("month" not in paramData) or\
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("png" not in paramData) or \
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("outParam" not in paramData):
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print(f'{argfile}中的参数有误，请核实！')
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return
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dataFile = paramData["dataFile"]
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freq = float(paramData["freq"])
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depth = float(paramData["depth"])
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windSpeed = float(paramData["windSpeed"])
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month = int(paramData["month"])
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png = paramData["png"]
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outParam = paramData["outParam"]
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from pyat.WGNPd import WGNPd
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from pyat.DataBase import DataBase
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import matplotlib.pyplot as plt
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import numpy as np
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freq = 50 * np.power(2, np.arange(freq)/3)
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frequency, spl = WGNPd(dataFile, depth, windSpeed, month, freq)
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#输出json文件
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outData = {}
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outData["param"] = paramData
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outData["descript"] = "frequency and noise level"
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frequency = np.around(frequency, decimals=0)
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spl = np.around(spl, decimals=2)
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outData["data"] = list(zip(frequency, spl))
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with open(("" if outParam["outPath"]=="" else outParam["outPath"] + "/")+"wgnpOut.json", 'w') as jsonFile:
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json.dump(outData, jsonFile, indent=2, ensure_ascii=False)
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if png:
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plt.semilogx(freq, spl)
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plt.xlabel('Frequency / Hz')
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plt.ylabel('Noise Level / dB')
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plt.show()
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if __name__ == '__main__':
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main() |