code: def test_estimate_heatmaps_norm_type(self):
      ntype = normalization.estimate_heatmaps_norm_type(None)
      assert ntype == "None"
  
      ntype = normalization.estimate_heatmaps_norm_type(
          np.zeros((1, 1, 1, 1), dtype=np.float32)
      )
      assert ntype == "array[float]"
  
      ntype = normalization.estimate_heatmaps_norm_type(
          ia.HeatmapsOnImage(
              np.zeros((1, 1, 1), dtype=np.float32), shape=(1, 1, 1)
          )
      )
      assert ntype == "HeatmapsOnImage"
  
      ntype = normalization.estimate_heatmaps_norm_type([])
      assert ntype == "iterable[empty]"
  
      ntype = normalization.estimate_heatmaps_norm_type(
          [np.zeros((1, 1, 1), dtype=np.float32)]
      )
      assert ntype == "iterable-array[float]"
  
      ntype = normalization.estimate_heatmaps_norm_type(
          [
              ia.HeatmapsOnImage(
                  np.zeros((1, 1, 1), dtype=np.float32), shape=(1, 1, 1)
              )
          ]
      )
      assert ntype == "iterable-HeatmapsOnImage"
  
      # --
      # error cases
      # --
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type(1)
  
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type("foo")
  
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type(
              np.zeros((1, 1, 1), dtype=np.int32)
          )
  
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type([1])
  
      # wrong class
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type(
              ia.KeypointsOnImage([], shape=(1, 1, 1))
          )
  
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type([[]])
  
      # list of list of Heatmaps, only list of Heatmaps is max
      with self.assertRaises(AssertionError):
          _ntype = normalization.estimate_heatmaps_norm_type(
              [
                  [
                      ia.HeatmapsOnImage(
                          np.zeros((1, 1, 1), dtype=np.float32),
                          shape=(1, 1, 1),
                      )
                  ]
              ]
          )
  
imports: from __future__ import print_function, division, absolute_import
  import sys
  import numpy
  import six.moves
  import imgaug
  import imgaug.augmentables.normalization
  from imgaug.testutils import reseed
label_desc: Use image node_id 18 for calling the TestNormalization obj's underlying member method code with example usage: obj.test_estimate_heatmaps_norm_type() without return types