code: def compute_gain_test_data(self):
      innovation_cov = 3 * gs.eye(1)
      data = [
          dict(
              prior_values=gs.eye(2),
              process_values=gs.eye(1),
              obs_values=2.0 * gs.eye(1),
              expected=gs.vstack(
                  (1.0 / innovation_cov, gs.zeros_like(innovation_cov))
              ),
          )
      ]
  
      return self.generate_tests(data)
  
imports: import geomstats.backend
  from geomstats.algebra_utils import from_vector_to_diagonal_matrix
  from geomstats.test.data import TestData
label_desc: Use image node_id 1 for calling the KalmanFilterTestData obj's underlying member method code with example usage: obj.compute_gain_test_data() and returns: self