code: def entropy(x):
      """The entropy of x as if x is a probability distribution"""
      histogram = scind.histogram(
          x.astype(float), np.min(x), np.max(x), 256
      )
      n = np.sum(histogram)
      if n > 0 and np.max(histogram) > 0:
          histogram = histogram[histogram != 0]
          return np.log2(n) - np.sum(histogram * np.log2(histogram)) / n
      else:
          return 0
  
imports: import numpy
  import scipy.ndimage
  import scipy.sparse
  from centrosome.filter import stretch
  from scipy.fftpack import fft2, ifft2
  from ..constants.measurement import COLTYPE_INTEGER
  from ..image import Image
  from ..module import Module
  from ..setting import Divider, SettingsGroup
  from ..setting.choice import Choice
  from ..setting.do_something import DoSomething, RemoveSettingButton
  from ..setting.subscriber import ImageSubscriber
  from ..setting.text import ImageName
label_desc: Use image node_id 3 for calling a global function with example usage: entropy(x) and returns: unknown, int