code: def test_hasher_alternate_sign():
      X = [list("Thequickbrownfoxjumped")]
  
      Xt = FeatureHasher(
          alternate_sign=True, input_type="string"
      ).fit_transform(X)
      assert Xt.data.min() < 0 and Xt.data.max() > 0
  
      Xt = FeatureHasher(
          alternate_sign=False, input_type="string"
      ).fit_transform(X)
      assert Xt.data.min() > 0
  
file_path: scikit-learn/sklearn/feature_extraction/tests/test_feature_hasher.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn.feature_extraction import FeatureHasher
  from sklearn.feature_extraction._hashing_fast import transform
label_desc: Use image node_id 9 for calling a global function with example usage: test_hasher_alternate_sign() without return types