code: def exp_test_data(self):
      smoke_data = [
          dict(
              tangent_vec=gs.array([[2.0, 0.0], [0.0, 2.0]]),
              base_point=gs.array([[0.0, 0.0], [0.0, 0.0]]),
              expected=gs.array(
                  [
                      [(EXP_4 - 1) / (EXP_4 + 1), 0.0],
                      [0.0, (EXP_4 - 1) / (EXP_4 + 1)],
                  ]
              ),
          ),
          dict(
              tangent_vec=gs.array([[2j, 0j], [0j, 2j]]),
              base_point=gs.array([[0j, 0j], [0j, 0j]]),
              expected=gs.array(
                  [
                      [(EXP_4 - 1) / (EXP_4 + 1) * 1j, 0j],
                      [0j, (EXP_4 - 1) / (EXP_4 + 1) * 1j],
                  ]
              ),
          ),
          dict(
              tangent_vec=gs.array([[0j, 0j], [0j, 0j]]),
              base_point=gs.array([[0j, 0j], [0j, 0j]]),
              expected=gs.array([[0j, 0j], [0j, 0j]]),
          ),
      ]
      return self.generate_tests(smoke_data)
  
imports: import math
  import geomstats.backend
  from geomstats.test.data import TestData
  from .complex_riemannian_metric import ComplexRiemannianMetricTestData
label_desc: Use image node_id 1 for calling the Siegel2MetricTestData obj's underlying member method code with example usage: obj.exp_test_data() and returns: self