code: def adjust_gain(signal, gain):
      """ "
      Adjust the gain of the signal.
  
      Parameters
      ----------
      signal : numpy array
          Signal to be adjusted.
      gain : float
          Gain adjustment level [dB].
  
      Returns
      -------
      numpy array
          Signal with adjusted gain.
  
      Notes
      -----
      The signal is returned with the same dtype, thus rounding errors may occur
      with integer dtypes.
  
      `gain` values > 0 amplify the signal and are only supported for signals
      with float dtype to prevent clipping and integer overflows.
  
      """
      # convert the gain in dB to a scaling factor
      gain = np.power(np.sqrt(10.0), 0.1 * gain)
      # prevent overflow and clipping
      if gain > 1 and np.issubdtype(signal.dtype, np.integer):
          raise ValueError(
              "positive gain adjustments are only supported for "
              "float dtypes."
          )
      # Note: np.asanyarray returns the signal's ndarray subclass
      return np.asanyarray(signal * gain, dtype=signal.dtype)
  
imports: from __future__ import absolute_import, division, print_function
  import warnings
  import numpy
  from ..processors import BufferProcessor, Processor
  from ..utils import integer_types
label_desc: Use image node_id 2 for calling a global function with example usage: adjust_gain(signal, gain) and returns: np