code: def test_sparse():
      copy = CopyTransformer()
      tfidf = TfidfTransformer()
      X_t = tfidf.fit_transform([[1, 2, 3]])
      assert issparse(X_t)
      X_dense = copy.transform(X_t).toarray()
      expect = np.array([[0.26726124, 0.53452248, 0.80178373]])
      assert np.allclose(X_dense, expect)
  
file_path: mlxtend/mlxtend/preprocessing/tests/test_copy_transformer.py
imports: import sys
  import numpy
  from packaging.version import Version
  from scipy.sparse import issparse
  from sklearn import __version__
  from sklearn.datasets import load_iris
  from sklearn.feature_extraction.text import TfidfTransformer
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from mlxtend.preprocessing import CopyTransformer
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 4 for calling a global function with example usage: test_sparse() without return types