class_docstr: Abstract base class for colored noise
  
  This contains several noise generator that generating different colored
  noise given the desired type and the length of clip data for degrading
code: def __init__(
      self,
      n_samples,
      color=None,
      weight_min=0.1,
      weight_max=0.5,
      rng=None,
  ):
      if n_samples <= 0:
          raise ValueError("n_samples must be strictly positive")
  
      if not 0 < weight_min < weight_max < 1.0:
          raise ValueError("weights must be in the range (0.0, 1.0)")
  
      BaseTransformer.__init__(self)
  
      self.n_samples = n_samples
      self.color = color
      self.weight_min = weight_min
      self.weight_max = weight_max
      self.rng = rng
      self._rng = _get_rng(rng)
  
file_path: muda/muda/deformers/colorednoise.py
imports: import numpy
  import librosa
  from ..base import BaseTransformer, _get_rng
label_desc: Use image node_id 1 to create a new ColoredNoise object from inherited base classes: BaseTransformer with example: obj = ColoredNoise(n_samples, color, weight_min, weight_max, rng)