code: def __call__(self, data, clip=None):
      mask = np.ma.getmask(data)
      result = self.process_value(data)[0]
      # Preserve the mask after normalization if there is one
      return np.ma.masked_array(result, mask)
  
imports: import warnings
  from matplotlib.image import _ImageBase
  from matplotlib.patches import Patch
  from matplotlib.transforms import Bbox, TransformedBbox, BboxTransform
  import matplotlib
  import numpy
  from .None import reductions
  from .None import transfer_functions
  from .colors import Sets1to3
  from .core import bypixel, Canvas
label_desc: Use image node_id 3 for calling the EqHistNormalize obj's underlying member method code with example usage: obj.__call__(data, clip) and returns: np