code: def test_non_distributional_model(my_data):
      # Plain model
      formula = bmb.Formula("y ~ x")
      model = bmb.Model(formula, my_data)
      idata = model.fit(tune=100, draws=100)
      model.predict(idata)
  
      assert list(idata.posterior.coords) == ["chain", "draw", "y_obs"]
      assert set(idata.posterior.data_vars) == {
          "Intercept",
          "x",
          "y_mean",
          "y_sigma",
      }
      assert list(idata.posterior["y_mean"].coords) == [
          "chain",
          "draw",
          "y_obs",
      ]
  
      # Model with alises
      model.set_alias(
          {"Intercept": "a", "x": "b", "sigma": "s", "y": "response"}
      )
      idata = model.fit(tune=100, draws=100)
      model.predict(idata)
      assert list(idata.posterior.coords) == [
          "chain",
          "draw",
          "response_obs",
      ]
      assert set(idata.posterior.data_vars) == {
          "a",
          "b",
          "response_mean",
          "s",
      }
      assert list(idata.posterior["response_mean"].coords) == [
          "chain",
          "draw",
          "response_obs",
      ]
  
file_path: bambi/tests/test_aliases.py
imports: import pytest
  import bambi
  import numpy
  import pandas
label_desc: Use image node_id 4 for calling a global function with example usage: test_non_distributional_model(my_data) without return types