class_docstr: Flip the audio samples upside-down, reversing their polarity. In other words, multiply the
  waveform by -1, so negative values become positive, and vice versa. The result will sound
  the same compared to the original when played back in isolation. However, when mixed with
  other audio sources, the result may be different. This waveform inversion technique
  is sometimes used for audio cancellation or obtaining the difference between two waveforms.
  However, in the context of audio data augmentation, this transform can be useful when
  training phase-aware machine learning models.
docstr: :param p: The probability of applying this transform
docstr_tok: [":","param","p",":","The","probability","of","applying","this","transform"]
code: def __init__(self, p: float = 0.5):
      """
      :param p: The probability of applying this transform
      """
      super().__init__(p)
  
file_path: audiomentations/audiomentations/augmentations/polarity_inversion.py
imports: import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
label_desc: Use image node_id 1 to create a new PolarityInversion object from inherited base classes: BaseWaveformTransform with example: obj = PolarityInversion(p)