code: def belongs_test_data(self):
      smoke_data = []
  
      split_sets = ((((0,), (1,)),),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=2, partition=((0, 1),), split_sets=split_sets
      )
      x = gs.array([0.3])
      point = self._Point(topology=top, weights=x)
  
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=True)
      )
      smoke_data.append(
          dict(space_args=(3,), points=point, expected=False)
      )
  
      top = Topology(n_labels=2, partition=((0, 1),), split_sets=((),))
      x = gs.array([])
      point = Wald(topology=top, weights=x)
  
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=False)
      )
      smoke_data.append(
          dict(space_args=(3,), points=point, expected=False)
      )
      smoke_data.append(
          dict(
              space_args=(top.n_labels,), points=[point], expected=False
          )
      )
      smoke_data.append(
          dict(
              space_args=(top.n_labels,), points=point, expected=[False]
          )
      )
      smoke_data.append(
          dict(
              space_args=(top.n_labels,),
              points=[point],
              expected=[False],
          )
      )
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)), ((0, 2), (1,))),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.1, 0.2])
      point = Wald(topology=top, weights=x)
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=True)
      )
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)),),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.1])
      point = Wald(topology=top, weights=x)
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=False)
      )
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)), ((0, 2), (1,))),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.0, 0.2])
      point = Wald(topology=top, weights=x)
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=False)
      )
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)), ((0, 2), (1,))),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.1, 1.0])
      point = Wald(topology=top, weights=x)
      smoke_data.append(
          dict(space_args=(top.n_labels,), points=point, expected=False)
      )
  
      points = []
      expected = []
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)), ((0, 2), (1,))),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.1, 0.2])
      point = Wald(topology=top, weights=x)
      points.append(point)
      expected.append(True)
  
      partition = ((0, 1, 2),)
      split_sets = ((((0, 1), (2,)),),)
      split_sets = [
          [Split(a, b) for a, b in splits] for splits in split_sets
      ]
      top = Topology(
          n_labels=3, partition=partition, split_sets=split_sets
      )
      x = gs.array([0.1])
      point = Wald(topology=top, weights=x)
      points.append(point)
      expected.append(False)
  
      smoke_data.append(
          dict(space_args=(3,), points=points, expected=expected)
      )
      return self.generate_tests(smoke_data)
  
imports: import random
  import geomstats.backend
  from geomstats.geometry.stratified.wald_space import Split, Topology, Wald, WaldSpace
  from geomstats.test.data import TestData
  from geomstats.test.test_case import np_backend
  from .point_set import PointSetTestData, PointTestData
label_desc: Use image node_id 1 for calling the WaldSpaceTestData obj's underlying member method code with example usage: obj.belongs_test_data() and returns: self