First commit after changed file framework

oanp.py

@@ -0,0 +1,59 @@
+# -*- coding: utf-8 -*-
+import warnings
+warnings.filterwarnings('ignore')
+import argparse, json
+from common import NoIndent, MyEncoder
+
+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 pyat.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()