def __calculate(self, spectrum, start, end):
sweep = slice_spectrum(spectrum, start, end)
if sweep is None or len(sweep) == 0:
return
self.minF = min(sweep)[0]
self.maxF = max(sweep)[0]
self.minP = min(sweep, key=lambda v: v[1])
self.maxP = max(sweep, key=lambda v: v[1])
powers = [Decimal(db_to_level(p[1])) for p in sweep]
length = len(powers)
avg = sum(powers, Decimal(0)) / length
self.avgP = level_to_db(avg)
product = reduce(mul, iter(powers))
gMean = product**(Decimal(1.0) / length)
self.gMeanP = level_to_db(gMean)
self.flatness = gMean / avg
self.__calc_hbw(sweep)
self.__calc_obw(sweep)
self.isValid = True
def __calculate(self, spectrum, start, end):
sweep = slice_spectrum(spectrum, start, end)
if sweep is None or len(sweep) == 0:
return
self.minF = min(sweep)[0]
self.maxF = max(sweep)[0]
self.minP = min(sweep, key=lambda v: v[1])
self.maxP = max(sweep, key=lambda v: v[1])
powers = [Decimal(db_to_level(p[1])) for p in sweep]
length = len(powers)
avg = sum(powers, Decimal(0)) / length
self.avgP = level_to_db(avg)
product = reduce(mul, iter(powers))
gMean = product ** (Decimal(1.0) / length)
self.gMeanP = level_to_db(gMean)
self.flatness = gMean / avg
self.__calc_hbw(sweep)
self.__calc_obw(sweep)
self.isValid = True