class_docstr: Gain up or down the audio after the given transform (or set of transforms) has
  processed the audio. There are several methods that determine how the audio should
  be gained. PostGain can be useful for compensating for any gain differences introduced
  by a (set of) transform(s), or for preventing clipping in the output.
class_docstr_tok: ["Gain","up","or","down","the","audio","after","the","given","transform","(","or","set","of","transforms",")","has","processed","the","audio",".","There","are","several","methods","that","determine","how","the","audio","should","be","gained",".","PostGain","can","be","useful","for","compensating","for","any","gain","differences","introduced","by","a","(","set","of",")","transform","(","s",")",",","or","for","preventing","clipping","in","the","output","."]
code: def __call__(
      self, samples: NDArray[np.float32], sample_rate: int
  ) -> NDArray[np.float32]:
      if self.method == "same_rms":
          return self.method_same_rms(samples, sample_rate)
      elif self.method == "same_lufs":
          return self.method_same_lufs(samples, sample_rate)
      elif self.method == "peak_normalize_always":
          return self.method_peak_normalize_always(samples, sample_rate)
      elif self.method == "peak_normalize_if_too_loud":
          return self.method_peak_normalize_if_too_loud(
              samples, sample_rate
          )
      else:
          raise Exception()
  
file_path: audiomentations/audiomentations/core/post_gain.py
imports: from typing import Callable
  import numpy
  import sys
  from numpy.typing import NDArray
  from audiomentations import Normalize
  from audiomentations.core.utils import calculate_rms, convert_decibels_to_amplitude_ratio
label_desc: Use image node_id 6 for calling the PostGain obj's underlying member method code with example usage: obj.__call__(samples, sample_rate) and returns: self, self, self, self