high_start = mid_start + int(sample_count * mid)
noise_ceiling = high_start + int(sample_count * high)
- amp_low = numpy.mean(magnitude[self.noise_floor:mid_start])
+ amp_low = numpy.mean(magnitude[noise_floor:mid_start])
amp_mid = numpy.mean(magnitude[mid_start:high_start])
amp_high = numpy.mean(magnitude[high_start:noise_ceiling])
- amp_total = (low + mid + high) / 3.0
+ amp_total = (amp_low + amp_mid + amp_high) / 3.0
return amp_low, amp_mid, amp_high, amp_total