code: def fit_test_data(self):
      smoke_data = []
      for metric, estimator in zip(self.metrics, self.estimators):
          init_point, end_point = metric._space.random_point(2)
          geo = metric.geodesic(init_point, end_point)
  
          s = gs.linspace(0.0, 1.0, self.n_points)
          points = geo(s)
  
          datum = dict(estimator=estimator, X=points)
          smoke_data.append(datum)
  
      return smoke_data
  
imports: import geomstats.backend
  from geomstats.geometry.stratified.graph_space import ExhaustiveAligner, GraphSpace, _GeodesicToPointAligner
  from geomstats.learning.aac import _AACGGPCA, _AACFrechetMean, _AACRegression
  from geomstats.test.data import TestData
  from geomstats.test.test_case import np_backend
label_desc: Use image node_id 2 for calling the _TrivialGeodesicData obj's underlying member method code with example usage: obj.fit_test_data() and returns: smoke_data