Source code for nussl.separation.benchmark.high_low_pass_filter

import numpy as np

from .. import MaskSeparationBase

[docs]class HighLowPassFilter(MaskSeparationBase): """ Implements a super simple separation algorithm that just masks everything below the specified hz. It does this by zeroing out the associated FFT bins via a mask to produce the "high" source, and the residual is the "low" source. Args: input_audio_signal (AudioSignal): Signal to separate. high_pass_cutoff_hz (float): Cutoff in Hz. Will be rounded off mask_type (str, optional): Mask type. Defaults to 'binary'. """ def __init__(self, input_audio_signal, high_pass_cutoff_hz, mask_type='binary'): super().__init__(input_audio_signal=input_audio_signal, mask_type=mask_type) self.high_pass_cutoff_hz = high_pass_cutoff_hz def run(self): # Compute the spectrogram and find the closest frequency bin to the cutoff freq closest_freq_bin = ( np.abs(self.audio_signal.freq_vector - self.high_pass_cutoff_hz) ).argmin() # Make masks low_pass_mask = self.ones_mask(self.stft.shape) low_pass_mask.mask[closest_freq_bin:, ...] = 0 high_pass_mask = low_pass_mask.invert_mask() self.result_masks = [low_pass_mask, high_pass_mask] return self.result_masks