code: def radon_contextual_effects_indiana_halfnormal():
      """Hierarchical radon model with contextual effects, with data from Indiana.
  
      Returns:
        target: StanModel.
      """
      dataset = data.radon_indiana()
      for key in list(dataset.keys()):
          if key.startswith("test_"):
              del dataset[key]
      return (
          radon_contextual_effects_halfnormal.radon_contextual_effects(
              **dataset
          )
      )
  
imports: from inference_gym.internal import data
  from inference_gym.tools.stan import brownian_motion
  from inference_gym.tools.stan import eight_schools
  from inference_gym.tools.stan import item_response_theory
  from inference_gym.tools.stan import log_gaussian_cox_process
  from inference_gym.tools.stan import logistic_regression
  from inference_gym.tools.stan import lorenz_system
  from inference_gym.tools.stan import probit_regression
  from inference_gym.tools.stan import radon_contextual_effects
  from inference_gym.tools.stan import radon_contextual_effects_halfnormal
  from inference_gym.tools.stan import sparse_logistic_regression
  from inference_gym.tools.stan import stochastic_volatility
label_desc: Use image node_id 10 for calling a global function with example usage: radon_contextual_effects_indiana_halfnormal() and returns: radon_contextual_effects_halfnormal