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
Test that the actual results are the expected ones.
pyts/transformation/tests/test_boss.py