# -*- coding: utf-8 -*-
import warnings
warnings.filterwarnings('ignore')
import argparse, json
from common import NoIndent, MyEncoder
import os, sys
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))+'/pyat')

def _argparse():
    parser = argparse.ArgumentParser(description='Average Noise Spectral Level')
    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 ("soundFile" not in paramData) or ("sense" not in paramData) or\
            ("filter" 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
        soundFile = paramData["soundFile"]
        M = float(paramData["sense"])
        A = float(paramData["filter"])
        png = paramData["png"]
        outParam = paramData["outParam"]
    
        from OANPd import call_oanp
        from matplotlib import pyplot as plt
        import numpy as np
        
        [freq, spl, fC, spl_oct] = call_oanp(soundFile=soundFile, M=M , A=A)
        # call_oanp(soundFile="./SAW2577_20200923_150000.wav", W=-164.0 , A=0, isPlot=isPlot)

        #输出json文件
        outData = {}
        outData["param"] = paramData
        outData["descript"] = "frequency and noise level"
        outData["count"] = len(fC)
        fC = np.around(fC, decimals=0)
        spl_oct = np.around(spl_oct, decimals=2)
        outData["data"] = NoIndent(list(zip(fC,spl_oct)))
        with open(("" if outParam["outPath"]=="" else outParam["outPath"] + "/")+"oanpOut.json", 'w') as jsonFile:
            json_data = json.dumps(outData, cls=MyEncoder, indent=2, ensure_ascii=False)
            jsonFile.write(json_data)

        if png:
            plt.semilogx(freq[20:10000], spl[20:10000])
            plt.semilogx(fC, spl_oct)
            plt.xlabel("Frequency / Hz")
            plt.ylabel("Noise Level / dB")
            plt.show()
    
if __name__ == '__main__':
    main()