code: def __init__(
      self,
      vmin=None,
      vmax=None,
      clip=False,
      nbins=256**2,
      ncolors=256,
  ):
      super(EqHistNormalize, self).__init__(vmin, vmax, clip)
      self._nbins = nbins
      self._bin_edges = None
      self._ncolors = ncolors
      self._color_bins = np.linspace(0, 1, ncolors)
  
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 1 to create a new EqHistNormalize object from inherited base classes: mpl.colors with example: obj = EqHistNormalize(vmin, vmax, clip, nbins, ncolors)