plot ( mean_freq_noise, label = "Mean power of noise" ) plt_std, = ax. subplots ( ncols = 2, figsize = ( 20, 4 )) plt_mean, = ax. show () def plot_statistics_and_filter ( mean_freq_noise, std_freq_noise, noise_thresh, smoothing_filter ): fig, ax = plt. matshow ( signal, origin = "lower", aspect = "auto", cmap = plt. subplots ( figsize = ( 20, 4 )) cax = ax. db_to_amplitude ( x, ref = 1.0 ) def plot_spectrogram ( signal, title ): fig, ax = plt. amplitude_to_db ( x, ref = 1.0, amin = 1e-20, top_db = 80.0 ) def _db_to_amp ( x ,): return librosa. istft ( y, hop_length, win_length ) def _amp_to_db ( x ): return librosa. stft ( y = y, n_fft = n_fft, hop_length = hop_length, win_length = win_length ) def _istft ( y, hop_length, win_length ): return librosa. Import time from datetime import timedelta as td def _stft ( y, n_fft, hop_length, win_length ): return librosa.
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