59 lines
2.3 KiB
Python
59 lines
2.3 KiB
Python
from __future__ import print_function
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import numpy as np
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import config
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import melbank
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class ExpFilter:
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"""Simple exponential smoothing filter"""
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def __init__(self, val=0.0, alpha_decay=0.5, alpha_rise=0.5):
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"""Small rise / decay factors = more smoothing"""
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assert 0.0 < alpha_decay < 1.0, 'Invalid decay smoothing factor'
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assert 0.0 < alpha_rise < 1.0, 'Invalid rise smoothing factor'
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self.alpha_decay = alpha_decay
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self.alpha_rise = alpha_rise
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self.value = val
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def update(self, value):
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if isinstance(self.value, (list, np.ndarray, tuple)):
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alpha = value - self.value
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alpha[alpha > 0.0] = self.alpha_rise
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alpha[alpha <= 0.0] = self.alpha_decay
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else:
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alpha = self.alpha_rise if value > self.value else self.alpha_decay
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self.value = alpha * value + (1.0 - alpha) * self.value
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return self.value
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def rfft(data, window=None):
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window = 1.0 if window is None else window(len(data))
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ys = np.abs(np.fft.rfft(data * window))
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xs = np.fft.rfftfreq(len(data), 1.0 / config.MIC_RATE)
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return xs, ys
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def fft(data, window=None):
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window = 1.0 if window is None else window(len(data))
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ys = np.fft.fft(data * window)
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xs = np.fft.fftfreq(len(data), 1.0 / config.MIC_RATE)
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return xs, ys
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samples = int(round(config.MIC_RATE * config.N_ROLLING_HISTORY / (2.0 * config.FPS)))
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mel_y, (_, mel_x) = melbank.compute_melmat(num_mel_bands=config.N_FFT_BINS,
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freq_min=config.MIN_FREQUENCY,
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freq_max=config.MAX_FREQUENCY,
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num_fft_bands=samples,
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sample_rate=config.MIC_RATE)
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def create_mel_bank(n_history):
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global samples, mel_y, mel_x
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config.N_ROLLING_HISTORY = n_history
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samples = int(round(config.MIC_RATE * config.N_ROLLING_HISTORY / (2.0 * config.FPS)))
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mel_y, (_, mel_x) = melbank.compute_melmat(num_mel_bands=config.N_FFT_BINS,
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freq_min=config.MIN_FREQUENCY,
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freq_max=config.MAX_FREQUENCY,
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num_fft_bands=samples,
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sample_rate=config.MIC_RATE)
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