59 行
2.2 KiB
Python
59 行
2.2 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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from common import NoIndent, MyEncoder
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def _argparse():
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parser = argparse.ArgumentParser(description='Average Noise Spectral Level')
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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 ("soundFile" not in paramData) or ("sense" not in paramData) or\
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("filter" not in paramData) or ("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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soundFile = paramData["soundFile"]
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M = float(paramData["sense"])
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A = float(paramData["filter"])
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png = paramData["png"]
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outParam = paramData["outParam"]
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from pyat.OANPd import call_oanp
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from matplotlib import pyplot as plt
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import numpy as np
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[freq, spl, fC, spl_oct] = call_oanp(soundFile=soundFile, M=M , A=A)
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# call_oanp(soundFile="./SAW2577_20200923_150000.wav", W=-164.0 , A=0, isPlot=isPlot)
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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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outData["count"] = len(fC)
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fC = np.around(fC, decimals=0)
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spl_oct = np.around(spl_oct, decimals=2)
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outData["data"] = NoIndent(list(zip(fC,spl_oct)))
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with open(("" if outParam["outPath"]=="" else outParam["outPath"] + "/")+"oanpOut.json", 'w') as jsonFile:
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json_data = json.dumps(outData, cls=MyEncoder, indent=2, ensure_ascii=False)
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jsonFile.write(json_data)
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if png:
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plt.semilogx(freq[20:10000], spl[20:10000])
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plt.semilogx(fC, spl_oct)
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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() |