'Element of is well-defined for integral classifiers.'

def test_element_of_integral(self):

    class C(Classifier, ):
        dtype = int64_dtype
        missing_value = (-1)
        inputs = ()
        window_length = 0
    c = C()
    data = np.array([[(-1), 1, 0, 2], [3, 0, 1, 0], [(-5), 0, (-1), 0], [(-3), 1, 2, 2]], dtype=int64_dtype)
    terms = {}
    expected = {}
    for choices in [(0,), (0, 1), (0, 1, 2)]:
        terms[str(choices)] = c.element_of(choices)
        expected[str(choices)] = reduce(op.or_, ((data == elem) for elem in choices), np.zeros_like(data, dtype=bool))
    self.check_terms(terms=terms, expected=expected, initial_workspace={c: data}, mask=self.build_mask(self.ones_mask(shape=data.shape)))
