code: def test_accurate_results_without_numerosity_reduction():
      """Test that the actual results are the expected ones."""
      boss = BOSS(
          word_size=4,
          n_bins=3,
          window_size=100,
          window_step=100,
          anova=False,
          drop_sum=False,
          norm_mean=False,
          norm_std=False,
          strategy="quantile",
          alphabet=None,
          numerosity_reduction=False,
      )
  
      X_windowed = X.reshape(8, 2, 100).reshape(16, 100)
      sfa = SymbolicFourierApproximation(
          n_coefs=4,
          drop_sum=False,
          anova=False,
          norm_mean=False,
          norm_std=False,
          n_bins=3,
          strategy="quantile",
          alphabet=None,
      )
      y_repeated = np.repeat(y, 2)
      X_sfa = sfa.fit_transform(X_windowed, y_repeated)
      X_word = np.asarray(["".join(X_sfa[i]) for i in range(16)])
      X_word = X_word.reshape(8, 2)
      X_bow = np.asarray([" ".join(X_word[i]) for i in range(8)])
  
      vectorizer = CountVectorizer()
      arr_desired = vectorizer.fit_transform(X_bow).toarray()
      vocabulary_desired = {
          value: key for key, value in vectorizer.vocabulary_.items()
      }
  
      arr_actual = boss.fit_transform(X, y).toarray()
      np.testing.assert_allclose(
          arr_actual, arr_desired, atol=1e-5, rtol=0
      )
      assert boss.vocabulary_ == vocabulary_desired
  
      arr_actual = boss.fit(X, y).transform(X).toarray()
      np.testing.assert_allclose(
          arr_actual, arr_desired, atol=1e-5, rtol=0
      )
      assert boss.vocabulary_ == vocabulary_desired
  
file_path: pyts/pyts/transformation/tests/test_boss.py
imports: import numpy
  import pytest
  import re
  from scipy.sparse import csr_matrix
  from sklearn.feature_extraction.text import CountVectorizer
  from pyts.transformation import BOSS
  from pyts.approximation import SymbolicFourierApproximation
label_desc: Use image node_id 3 for calling a global function with example usage: test_accurate_results_without_numerosity_reduction() without return types