code: def test_get_feature_names_out_featureunion():
      X, _ = make_classification(n_samples=10)
      pipeline = Pipeline(
          [
              (
                  "umap_pipeline",
                  FeatureUnion(
                      [
                          ("umap1", UMAP()),
                          ("umap2", UMAP(n_components=3)),
                      ]
                  ),
              )
          ]
      )
  
      pipeline.fit(X)
      feature_names = pipeline.get_feature_names_out()
      expected_feature_names = np.array(
          [
              "umap1__umap_component_1",
              "umap1__umap_component_2",
              "umap2__umap_component_1",
              "umap2__umap_component_2",
              "umap2__umap_component_3",
          ]
      )
      np.testing.assert_array_equal(
          feature_names, expected_feature_names
      )
  
file_path: umap/umap/tests/test_umap_get_feature_names_out.py
imports: import numpy
  from sklearn.datasets import make_classification
  from sklearn.pipeline import Pipeline, FeatureUnion
  from ..umap_ import UMAP
label_desc: Use image node_id 4 for calling a global function with example usage: test_get_feature_names_out_featureunion() without return types