def findserienum(self, datas, t_series):
t_lener = words_base()
t_dataone, t_datatwo = t_lener.get_seidinfo(datas)
j_one = base_analyzer.pearson(t_dataone, t_series)
j_two = base_analyzer.pearson(t_datatwo, t_series)
j_final = max(j_one, j_two)
return j_final
def inferLen(self, datas, lenDatas):
datasLenBig = Converter.bytesToBigInt(datas)
datasLittle = Converter.bytesToLittleInt(datas)
personBig = base_analyzer.pearson(datasLenBig, lenDatas)
personLittle = base_analyzer.pearson(datasLittle, lenDatas)
if personBig > self.lengthThreshold or personLittle > self.lengthThreshold:
return 1
else:
return 0
def inferSeriesId(self, datas):
ids = []
for i, data in enumerate(datas):
ids.append(i)
datasBigInt = Converter.bytesToBigInt(datas)
datasLittle = Converter.byteToLittle(datas)
tRate = max(base_analyzer.pearson(ids, datasBigInt),
base_analyzer.pearson(ids, datasLittle))
if (tRate > self.idThreshold):
return 1
else:
return 0
def inferLen(self, Los=None, datas=None):
if Los != None:
datas = self.cverter.getDatasByLocs(self.messages, Los)
lens = [len(data) for data in datas]
datasLenBig = Converter.bytesToBigInt(datas)
datasLittle = Converter.bytesToLittleInt(datas)
personBig = base_analyzer.pearson(datasLenBig, lens)
personLittle = base_analyzer.pearson(datasLittle, lens)
if personBig > self.lengthThreshold or personLittle > self.lengthThreshold:
return 1
else:
return 0
def inferSeriesId(self, Los=None, datas=None):
if Los != None:
datas = self.cverter.getDatasByLocs(self.messages, Los)
ids = []
for i, data in enumerate(datas):
ids.append(i)
datasBigInt = Converter.bytesToBigInt(datas)
datasLittle = Converter.bytesToLittleInt(datas)
tRate = max(base_analyzer.pearson(ids, datasBigInt),
base_analyzer.pearson(ids, datasLittle))
if (tRate > self.idThreshold):
return 1
else:
return 0