X-Git-Url: https://zdv2.bktei.com/gitweb/EVA-2020-02-2.git/blobdiff_plain/aa747a416652b64a182d6e2594c08e2476d17d76..f3e6204d564e95ac83bda4bcfa97f94ca1adddda:/library/enviroplus/noise.py diff --git a/library/enviroplus/noise.py b/library/enviroplus/noise.py index 57e869d..7b6d5e2 100644 --- a/library/enviroplus/noise.py +++ b/library/enviroplus/noise.py @@ -1,17 +1,27 @@ import sounddevice import numpy -import math + class Noise(): - def __init__( - self, - sample_rate=16000, - duration=0.5): + def __init__(self, + sample_rate=16000, + duration=0.5): + """Noise measurement. + + :param sample_rate: Sample rate in Hz + :param duraton: Duration, in seconds, of noise sample capture + + """ self.duration = duration self.sample_rate = sample_rate def get_amplitudes_at_frequency_ranges(self, ranges): + """Return the mean amplitude of frequencies in the given ranges. + + :param ranges: List of ranges including a start and end range + + """ recording = self._record() magnitude = numpy.abs(numpy.fft.rfft(recording[:, 0], n=self.sample_rate)) result = [] @@ -21,6 +31,12 @@ class Noise(): return result def get_amplitude_at_frequency_range(self, start, end): + """Return the mean amplitude of frequencies in the specified range. + + :param start: Start frequency (in Hz) + :param end: End frequency (in Hz) + + """ n = self.sample_rate // 2 if start > n or end > n: raise ValueError("Maxmimum frequency is {}".format(n)) @@ -29,12 +45,21 @@ class Noise(): magnitude = numpy.abs(numpy.fft.rfft(recording[:, 0], n=self.sample_rate)) return numpy.mean(magnitude[start:end]) - def get_noise_profile( - self, - noise_floor=100, - low=0.12, - mid=0.36, - high=None): + def get_noise_profile(self, + noise_floor=100, + low=0.12, + mid=0.36, + high=None): + """Returns a noise charateristic profile. + + Bins all frequencies into 3 weighted groups expressed as a percentage of the total frequency range. + + :param noise_floor: "High-pass" frequency, exclude frequencies below this value + :param low: Percentage of frequency ranges to count in the low bin (as a float, 0.5 = 50%) + :param mid: Percentage of frequency ranges to count in the mid bin (as a float, 0.5 = 50%) + :param high: Optional percentage for high bin, effectively creates a "Low-pass" if total percentage is less than 100% + + """ if high is None: high = 1.0 - low - mid @@ -48,10 +73,10 @@ class Noise(): 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 @@ -63,4 +88,3 @@ class Noise(): channels=1, dtype='float64' ) -