How to use the tpot.builtins.FeatureSetSelector function in TPOT

def test_FeatureSetSelector_3():
    """Assert that the StackingEstimator returns transformed X based on 2 subsets' names"""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset=["test_subset_1", "test_subset_2"])
    ds.fit(test_X, y=None)
    transformed_X = ds.transform(test_X)

    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 7
    assert np.array_equal(transformed_X, test_X[ds.feat_list].values)

def test_FeatureSetSelector_6():
    """Assert that the _get_support_mask function returns correct mask."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_1")
    ds.fit(test_X, y=None)
    mask = ds._get_support_mask()
    get_mask = ds.get_support()

    assert mask.shape[0] == 30
    assert np.count_nonzero(mask) == 5
    assert np.array_equal(get_mask, mask)

def test_FeatureSetSelector_4():
    """Assert that the StackingEstimator returns transformed X based on 2 subsets' indexs"""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset=[0, 1])
    ds.fit(test_X, y=None)
    transformed_X = ds.transform(test_X)

    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 7
    assert np.array_equal(transformed_X, test_X[ds.feat_list].values)

def test_FeatureSetSelector_2():
    """Assert that the StackingEstimator returns transformed X based on test feature list 2."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_2")
    ds.fit(test_X, y=None)
    transformed_X = ds.transform(test_X)

    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 6
    assert np.array_equal(transformed_X, test_X[ds.feat_list].values)

def test_FeatureSetSelector_7():
    """Assert that the StackingEstimator works as expected when input X is np.array."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_1")
    ds.fit(test_X.values, y=None)
    transformed_X = ds.transform(test_X.values)
    str_feat_list = [str(i+2) for i in ds.feat_list_idx]


    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 5
    assert np.array_equal(transformed_X, test_X.values[:, ds.feat_list_idx])
    assert np.array_equal(transformed_X, test_X[str_feat_list].values)

def test_FeatureSetSelector_5():
    """Assert that the StackingEstimator returns transformed X seleced based on test feature list 1's index."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset=0)
    ds.fit(test_X, y=None)
    transformed_X = ds.transform(test_X)

    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 5
    assert np.array_equal(transformed_X, test_X[ds.feat_list].values)

def test_FeatureSetSelector_1():
    """Assert that the StackingEstimator returns transformed X based on test feature list 1."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_1")
    ds.fit(test_X, y=None)
    transformed_X = ds.transform(test_X)

    assert transformed_X.shape[0] == test_X.shape[0]
    assert transformed_X.shape[1] != test_X.shape[1]
    assert transformed_X.shape[1] == 5
    assert np.array_equal(transformed_X, test_X[ds.feat_list].values)

def test_FeatureSetSelector_8():
    """Assert that the StackingEstimator rasies ValueError when features are not available."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_4")
    assert_raises(ValueError, ds.fit, test_X)

def test_FeatureSetSelector_9():
    """Assert that the StackingEstimator __name__ returns correct class name."""
    ds = FeatureSetSelector(subset_list="tests/subset_test.csv", sel_subset="test_subset_4")
    assert ds.__name__ == 'FeatureSetSelector'