code: def test_normal_sample():
      """Sample from normal distribution."""
      program_code = (
          "parameters {real y;} model {y ~ normal(0, 0.0001);}"
      )
      posterior = stan.build(program_code)
      assert posterior is not None
      fit = posterior.sample()
      offset = len(fit.sample_and_sampler_param_names)
      assert fit._draws.shape == (
          offset + 1,
          1000,
          4,
      )  # 4 chains, n samples, 1 param
      df = fit.to_frame()
      assert (df["y"] == fit._draws[offset, :, :].ravel()).all()
      assert len(df["y"]) == 4000
      assert -0.01 < df["y"].mean() < 0.01
      assert -0.01 < df["y"].std() < 0.01
  
imports: from math import ceil
  import stan
label_desc: Use image node_id 2 for calling a global function with example usage: test_normal_sample() without return types