code: def normalize(image, min_v=None, max_v=None, new_min=-1, new_max=1):
      r"""
      normalization function
  
      Parameters
      ----------
      image : np.ndarray
      min_v : int or float, optional
          minimum value range for normalization
          intensities below min_v will be clipped
          if None it is set to min value of image
          Default : None
      max_v : int or float, optional
          maximum value range for normalization
          intensities above max_v will be clipped
          if None it is set to max value of image
          Default : None
      new_min : int or float, optional
          new minimum value after normalization
          Default : 0
      new_max : int or float, optional
          new maximum value after normalization
          Default : 1
  
      Returns
      -------
      np.ndarray
          Normalized image from range new_min to new_max
      """
      if min_v is None:
          min_v = np.min(image)
      if max_v is None:
          max_v = np.max(image)
      return np.interp(image, (min_v, max_v), (new_min, new_max))
  
file_path: dipy/dipy/nn/utils.py
imports: import numpy
  from scipy.ndimage import affine_transform, label
  from dipy.align.reslice import reslice
label_desc: Use image node_id 1 for calling a global function with example usage: normalize(image, min_v, max_v, new_min, new_max) and returns: np