code: def test_fit_transform(params):
      """Test that 'fit_transform' and 'fit' then 'transform' yield same res."""
      weasel_1 = WEASEL(**params, sparse=False)
      weasel_2 = WEASEL(**params, sparse=False)
  
      X_fit_transform = weasel_1.fit_transform(X, y)
      X_fit_then_transform = weasel_2.fit(X, y).transform(X)
  
      # Test that the transformation are identical
      np.testing.assert_allclose(
          X_fit_transform, X_fit_then_transform, atol=1e-5, rtol=0.0
      )
  
      # Test that the vocabulary_ attributes are identical
      assert weasel_1.vocabulary_ == weasel_2.vocabulary_
  
file_path: pyts/pyts/transformation/tests/test_weasel.py
imports: import numpy
  import pytest
  import re
  from scipy.sparse import csr_matrix, hstack
  from sklearn.feature_extraction.text import CountVectorizer
  from sklearn.feature_selection import chi2
  from pyts.approximation import SymbolicFourierApproximation
  from pyts.transformation import WEASEL
label_desc: Use image node_id 3 for calling a global function with example usage: test_fit_transform(params) without return types