class_docstr: Distort signal by clipping a random percentage of points
  
  The percentage of points that will be clipped is drawn from a uniform distribution between
  the two input parameters min_percentile_threshold and max_percentile_threshold. If for instance
  30% is drawn, the samples are clipped if they're below the 15th or above the 85th percentile.
code: def randomize_parameters(
      self, samples: NDArray[np.float32], sample_rate: int
  ):
      super().randomize_parameters(samples, sample_rate)
      if self.parameters["should_apply"]:
          self.parameters["percentile_threshold"] = random.randint(
              self.min_percentile_threshold,
              self.max_percentile_threshold,
          )
  
file_path: audiomentations/audiomentations/augmentations/clipping_distortion.py
imports: import random
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
label_desc: Use image node_id 2 for calling the ClippingDistortion obj's underlying member method code with example usage: obj.randomize_parameters(samples, sample_rate) without return types