code: def test_matrices_from_component(self):
      num_timesteps = 4
      num_features = 3
      drift_scale = 1.23
  
      design_matrix = self._build_placeholder(
          np.random.randn(num_timesteps, num_features)
      )
  
      component = DynamicLinearRegression(design_matrix=design_matrix)
  
      ssm = component.make_state_space_model(
          num_timesteps, [drift_scale]
      )
  
      for t in range(num_timesteps):
          observation_matrix = self.evaluate(
              ssm.get_observation_matrix_for_timestep(t).to_dense()
          )
  
          self.assertAllClose(
              self.evaluate(design_matrix[tf.newaxis, t]),
              observation_matrix,
          )
  
          observation_noise_mean = self.evaluate(
              ssm.get_observation_noise_for_timestep(t).mean()
          )
          observation_noise_covariance = self.evaluate(
              ssm.get_observation_noise_for_timestep(t).covariance()
          )
  
          self.assertAllClose([0.0], observation_noise_mean)
          self.assertAllClose([[0.0]], observation_noise_covariance)
  
          transition_matrix = self.evaluate(
              ssm.get_transition_matrix_for_timestep(t).to_dense()
          )
  
          self.assertAllClose(np.eye(num_features), transition_matrix)
  
          transition_noise_mean = self.evaluate(
              ssm.get_transition_noise_for_timestep(t).mean()
          )
          transition_noise_covariance = self.evaluate(
              ssm.get_transition_noise_for_timestep(t).covariance()
          )
  
          self.assertAllClose(
              np.zeros([num_features]), transition_noise_mean
          )
          self.assertAllClose(
              np.square(drift_scale) * np.eye(num_features),
              transition_noise_covariance,
          )
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.sts.components.dynamic_regression import DynamicLinearRegression
  from tensorflow_probability.python.sts.components.dynamic_regression import DynamicLinearRegressionStateSpaceModel
label_desc: Use image node_id 3 for calling the _DynamicLinearRegressionStateSpaceModelTest obj's underlying member method code with example usage: obj.test_matrices_from_component() without return types