code: def log_test_data(self):
      smoke_data = [
          dict(
              point=gs.array([[0.5, 0.0], [0.0, 0.5]]),
              base_point=gs.array([[0.0, 0.0], [0.0, 0.0]]),
              expected=gs.array([[LN_3 / 2, 0.0], [0.0, LN_3 / 2]]),
          ),
          dict(
              point=gs.array([[0.5j, 0j], [0j, 0.5j]]),
              base_point=gs.array([[0j, 0j], [0j, 0j]]),
              expected=gs.array(
                  [[LN_3 / 2 * 1j, 0j], [0j, LN_3 / 2 * 1j]]
              ),
          ),
          dict(
              point=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 2 for calling the Siegel2MetricTestData obj's underlying member method code with example usage: obj.log_test_data() and returns: self