code: def compute_variance_from_index_test_data(self):
      data = [
          dict(
              weighted_distances=gs.array([0.5, 0.4, 0.3, 0.2]),
              expected_var=gs.array([0.481, 0.434, 0.378, 0.311]),
          )
      ]
      return self.generate_tests(data)
  
file_path: geomstats/tests/tests_geomstats/test_learning/data/expectation_maximization.py
imports: import geomstats.backend
  from geomstats.test.data import TestData
  from ._base import BaseEstimatorTestData
label_desc: Use image node_id 5 for calling the GaussianMixtureModelTestData obj's underlying member method code with example usage: obj.compute_variance_from_index_test_data() and returns: self