code: def normalize_qa(qa, max_qa=None):
      """Normalize quantitative anisotropy.
  
      Used mostly with GQI rather than GQI2.
  
      Parameters
      ----------
      qa : array, shape (X, Y, Z, N)
          where N is the maximum number of peaks stored
      max_qa : float,
          maximum qa value. Usually found in the CSF (corticospinal fluid).
  
      Returns
      -------
      nqa : array, shape (x, Y, Z, N)
          normalized quantitative anisotropy
  
      Notes
      -----
      Normalized quantitative anisotropy has the very useful property
      to be very small near gray matter and background areas. Therefore,
      it can be used to mask out white matter areas.
  
      """
      if max_qa is None:
          return qa / qa.max()
      return qa / max_qa
  
imports: import numpy
  from dipy.reconst.odf import OdfModel, OdfFit
  from dipy.reconst.cache import Cache
  import warnings
  from dipy.reconst.multi_voxel import multi_voxel_fit
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_qa(qa, max_qa) and returns: unknown, unknown