code: def fit_two_clusters_test_data(self):
      euclidean = Euclidean(dim=2)
      sphere = Hypersphere(dim=2)
  
      data = [
          dict(
              dataset=gs.array(
                  [[1, 2], [1, 4], [1, 0], [4, 2], [4, 4], [4, 0]]
              ),
              estimator=AgglomerativeHierarchicalClustering(
                  euclidean,
                  n_clusters=2,
              ),
              expected=gs.array([1, 1, 1, 0, 0, 0]),
          ),
          dict(
              dataset=gs.array(
                  [
                      [1, 0, 0],
                      [3 ** (1 / 2) / 2, 1 / 2, 0],
                      [3 ** (1 / 2) / 2, -1 / 2, 0],
                      [0, 0, 1],
                      [0, 1 / 2, 3 ** (1 / 2) / 2],
                      [0, -1 / 2, 3 ** (1 / 2) / 2],
                  ]
              ),
              estimator=AgglomerativeHierarchicalClustering(
                  sphere,
                  n_clusters=2,
              ),
              expected=gs.array([1, 1, 1, 0, 0, 0]),
          ),
      ]
      return self.generate_tests(data)
  
imports: import geomstats.backend
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.hypersphere import Hypersphere
  from geomstats.learning.agglomerative_hierarchical_clustering import AgglomerativeHierarchicalClustering
  from geomstats.test.data import TestData
label_desc: Use image node_id 1 for calling the AgglomerativeHierarchicalClusteringTestData obj's underlying member method code with example usage: obj.fit_two_clusters_test_data() and returns: self