code: def test_laplace():
      data = pd.DataFrame(np.repeat((0, 1), (30, 60)), columns=["w"])
      priors = {"Intercept": bmb.Prior("Uniform", lower=0, upper=1)}
      model = bmb.Model(
          "w ~ 1",
          data=data,
          family="bernoulli",
          priors=priors,
          link="identity",
      )
      results = model.fit(inference_method="laplace")
      mode_n = results.posterior["Intercept"].mean().item()
      std_n = results.posterior["Intercept"].std().item()
      mode_a = data.mean()
      std_a = data.std() / len(data) ** 0.5
      np.testing.assert_array_almost_equal(
          (mode_n, std_n), (mode_a.item(), std_a.item()), decimal=2
      )
  
file_path: bambi/tests/test_alternative_samplers.py
imports: import bambi
  import numpy
  import pandas
  import pytest
label_desc: Use image node_id 2 for calling a global function with example usage: test_laplace() without return types